Engineering AI Training Jobs - Compare Pay

SME

Electrical Engineer

SMEEngineering

Up to $100/hr

About this role

If you are an electrical engineer who thrives on technical precision, applied problem-solving, and rigorous reasoning across circuits, power, and systems, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex electrical engineering concepts. We are looking for electrical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as an Electrical Engineer will directly help improve the world’s premier AI models—and play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional electrical engineering experience, with significant hands-on work in one or more areas such as power systems, power electronics, industrial controls, embedded systems, analog/digital circuit design, RF/communications, signal processing, instrumentation, automation, electronics manufacturing/test, or a closely related specialty. - Deep knowledge of electrical engineering fundamentals, including circuit analysis, electronics, electromagnetics, signals & systems, control fundamentals, and safe engineering practices (grounding, isolation, protection, EMC/EMI). - Strong comfort with engineering calculations, assumptions, constraints, unit consistency, and defensible reasoning (including limitations and safety considerations). - Bachelor’s degree in Electrical Engineering (or closely related) required; Master’s/PhD, PE/Chartered, or advanced professional certifications strongly preferred. - Previous experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with tools/artifacts such as schematics, SPICE simulation, MATLAB/Simulink, PCB design, oscilloscopes/logic analyzers, power studies, or test reports is a plus. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across electrical engineering topics. - Challenge advanced language models with realistic electrical engineering scenarios, calculations, and standards-informed reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step solutions (including correct math, units, and assumptions). - Provide structured feedback that identifies factual errors, unsafe recommendations, missing constraints, invalid assumptions, incorrect modeling, or incomplete reasoning. - Assess model performance on topics such as: Circuit design/analysis, Power systems, Power electronics, Controls, Embedded & digital, EMI/EMC & safety, Test & troubleshooting - Help shape AI communication standards for technical EE content, including how models explain assumptions, limits, safety concerns, and professional judgment. - Ensure AI-generated content reflects responsible engineering practice—especially around electrical safety, compliance, and real-world feasibility. Additional skills - Power Systems - Power Electronics - Circuit Analysis - Analog Circuit Design - Digital Circuit Design - Embedded Systems - Industrial Controls - Automation - Instrumentation - Control Systems - Signals & Systems - Electromagnetics - RF Engineering - Communications Systems - Signal Processing - PCB Design - Schematic Capture - SPICE Simulation - MATLAB - Simulink - Oscilloscope - Logic Analyzer - EMC/EMI Compliance - Grounding & Bonding - Electrical Safety - Protection Systems - Power System Studies - Electronics Testing - Electronics Manufacturing - PE License

Mercor

Mechanical Engineering Writer

MercorEngineering / Writing & Editing2 days ago

$80/hr

Worldwide

Apply

About this role

Role Overview - Mercor is seeking senior mechanical engineering professionals to build evaluation tasks for AI systems operating in Fortune 500 enterprise product design and manufacturing contexts. - The workflows are calibrated to the design complexity, safety stakes, and production scale of Fortune 500 and large industrial manufacturers. - This role builds worlds on two standards tracks: a US track (ASME) and an International track (ISO). Experts qualified in either or both tracks are encouraged to apply. - Contributors design enterprise mechanical engineering scenarios, draft reference outputs, and write rubrics that capture how senior F500 engineering leaders think. Key Responsibilities - Construct enterprise mechanical engineering scenarios spanning complex product design cycles, multi-stakeholder design reviews, and manufacturing or regulatory certification processes at F500 accounts. - Build tasks across F500 product design and CAD modeling, thermal/fluid systems analysis, structural and stress analysis, manufacturing process engineering, and reliability/failure analysis. - Develop engineering scenarios involving tools such as SolidWorks, ANSYS, CATIA, MATLAB/Simulink, and enterprise PLM systems (Siemens Teamcenter, PTC Windchill) in F500 stacks. - Apply enterprise mechanical engineering methodologies (FEA/CFD simulation, DFM/DFA principles, Six Sigma/DFSS, GD&T per ASME Y14.5 or ISO GPS) and produce reference design specifications, engineering analyses, and executive-level technical narratives. - Author rubrics that distinguish authentic enterprise mechanical engineering judgment from generic textbook or coursework-level recall. Ideal Qualifications - 5+ years working as a mechanical engineer or engineering lead at a Fortune 500 or major industrial, automotive, aerospace, or manufacturing company (GE, Boeing, Caterpillar, Ford, Honeywell, Siemens, Bosch, Rolls-Royce, Mitsubishi Heavy Industries). - Direct ownership of large-scale product designs, manufacturing processes, or engineering certification programs. - Fluency in enterprise mechanical engineering tooling and methodologies, plus understanding of how safety standards, regulatory certification (ASME, ISO, FAA, FDA), and cross-functional design governance actually work. - A professional engineering credential (US PE or an international equivalent such as CEng or EUR ING) and prior rubric, engineering-training curriculum, or design documentation authorship are a plus.

SME

Biomedical Engineer

SMEEngineering

Up to $100/hr

Apply

About this role

If you are a biomedical engineer who thrives on technical precision, applied problem-solving, and rigorous engineering reasoning in health and life-science contexts, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex biomedical engineering concepts. We are looking for biomedical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Biomedical Engineer will directly help improve the world’s premier AI models—and play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional biomedical engineering experience, with significant hands-on work in one or more areas such as medical devices, biomechanics, biomaterials, tissue engineering, bioinstrumentation, imaging systems, signals & systems (physiologic), rehabilitation engineering, clinical engineering, quality/regulatory, manufacturing/validation, or a closely related specialty. - Deep knowledge of biomedical engineering fundamentals, such as physiology for engineers, transport phenomena in biological systems, biomechanics, materials behavior in biological environments, biosignals, sensor/measurement systems, and systems modeling (depending on specialty). - Strong comfort with technical assumptions, constraints, unit consistency, and defensible reasoning (including limitations, uncertainty, and safety considerations). - Bachelor’s degree in Biomedical Engineering (or closely related) required; Master’s/PhD or advanced credentials strongly preferred. - Experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with any of the following is a plus (not required): ISO 13485, IEC 60601, ISO 14971, FDA design controls (21 CFR 820), verification & validation, risk management, biocompatibility concepts (ISO 10993), or clinical workflow constraints. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across biomedical engineering topics. - Challenge advanced language models with realistic biomedical engineering scenarios, calculations, and design/analysis reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step solutions (including unit handling and correct interpretation of constraints). - Provide structured feedback that identifies factual errors, unsafe recommendations, unsupported clinical claims, missing assumptions, invalid simplifications, misuse of standards, or incomplete reasoning. - Assess model performance on topics such as: Biomechanics, Bioinstrumentation & sensors, Biomedical signals, Medical device design, Biomaterials, Imaging & measurement, Verification/validation & risk - Help shape AI communication standards for biomedical content, including how models explain assumptions, risk/limitations, what must be verified experimentally, and when to escalate to clinical/regulatory experts. - Ensure AI-generated content reflects responsible biomedical engineering practice—especially around patient safety, clinical claims, and regulatory-sensitive topics. Additional skills - Medical Device Design - Biomechanics - Biomaterials - Tissue Engineering - Bioinstrumentation - Physiological Signal Processing - Signals & Systems - Medical Imaging Systems - Rehabilitation Engineering - Clinical Engineering - Physiology - Transport Phenomena - Systems Modeling - Sensor Design - Data Acquisition (DAQ) - MATLAB - Python - LabVIEW - SolidWorks - Finite Element Analysis (FEA) - Design of Experiments (DoE) - Verification & Validation (V&V) - Risk Management (ISO 14971) - ISO 13485 - IEC 60601 - FDA Design Controls (21 CFR 820) - Biocompatibility (ISO 10993) - Quality Management Systems (QMS) - Manufacturing Validation - AI Data Annotation

Mercor

Mechanical Engineering Expert

MercorEngineering

$70-$125/hr

Worldwide

Apply

About this role

The research teams behind the best-known AI models come to Mercor for mechanical engineering judgment they can't generate on their own. Your standards and expertise become the rubric that frontier AI is graded against. This is a standing listing for mechanical engineers who want AI training and evaluation work, not a specific job opening. It stays open whether or not a matching project is running this week. New projects start on short notice, so instead of posting and pulling a listing each time, we keep one open per field and draw from it when one begins. What the work looks like We match mechanical engineers in the network to projects like: - Writing a design problem from work you have done, with the loads, the constraints, and the tolerances, plus the reference answer a model's attempt gets graded against - Grading model-written analysis: whether the free body diagram is right, whether the failure mode considered is the governing one, whether the safety factor is applied to the right quantity - Flagging where a model's design satisfies the calculation and fails in practice, given manufacturability, assembly, wear, or thermal expansion Past rates have run $70 to $125 an hour, set per project by scope and depth. What we're looking for - A degree in mechanical engineering, with professional design or analysis experience - Clear written communication, since most of the work involves explaining your reasoning - Comfort with ambiguous tasks, and willingness to flag unclear instructions Where you trained matters less than whether you have had a design of yours built, and learned what it did once it was. How it works Apply here with your resume and confirm where you work from, then take a short AI interview, about 20 minutes total. We verify your background and add you to the mechanical engineering pool. When a project needs mechanical engineering expertise, we invite matching people from the pool to that specific listing. It names the rate, the hours, and the client, and any hiring decision is made there. What to expect This listing does not accept or reject candidates, so you will not get a decision on it. We reach out when a project matches your background. Depending on what our clients are running, that can be within a week or several months. Finishing the domain expert interview and joining every network you qualify for both improve your odds of being matched. You only need to sign up once to be eligible across all of them.

SME

Chemical Engineer

SMEEngineering

Up to $100/hr

Apply

About this role

If you are a chemical engineer who thrives on technical precision, applied problem-solving, and real-world process reasoning, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex chemical engineering concepts. We are looking for chemical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Chemical Engineer will directly help improve the world’s premier AI models, and will play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional chemical engineering experience, with meaningful hands-on work in process design, plant/operations engineering, process safety, scale-up, manufacturing, utilities, EHS, quality, R&D, controls/automation interfaces, or a closely related chemical engineering specialty. - Deep knowledge of chemical engineering fundamentals, including material & energy balances, thermodynamics, fluid mechanics, heat & mass transfer, reaction engineering, separations (distillation, absorption, extraction, membranes), unit operations, and process control concepts. - Strong comfort with engineering calculations, assumptions, constraints, and defensible reasoning (including uncertainty, safety factors, and limitations). - Bachelor’s degree in Chemical Engineering (or closely related) required; Master’s/PhD, PE/Chartered credentials, or advanced professional certifications strongly preferred. - Previous experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with tools and artifacts such as PFDs/P&IDs, Aspen Plus/HYSYS, CHEMCAD, process datasheets, PSM documentation, HAZOP/LOPA, or SOPs is a plus. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across chemical engineering topics. - Challenge advanced language models with realistic chemical engineering scenarios, calculations, and process-informed reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step engineering solutions. - Provide structured feedback that identifies factual errors, flawed assumptions, missing constraints, unsafe recommendations, unit/consistency mistakes, or incomplete reasoning. - Assess model performance on topics such as: Material & energy balances, phase behavior, and thermodynamic property use, Unit operations and sizing logic, Distillation/separations design logic and feasibility checks, Process control reasoning, Process safety, Scale-up/manufacturability, operability, and troubleshooting of plant scenarios - Help shape AI communication standards for technical chemical engineering content, including how models explain assumptions, limitations, calculations, and professional judgment. - Ensure AI-generated content reflects sound engineering principles, appropriate safety considerations, and responsible technical communication (including “when to escalate to a licensed engineer/site expert”). Additional skills - Process Design - Plant Engineering - Process Safety Management (PSM) - Scale-Up Engineering - Manufacturing Engineering - Utilities Engineering - Environmental Health & Safety (EHS) - Quality Assurance (QA) - Research & Development (R&D) - Process Control - Controls & Automation - Material & Energy Balances - Thermodynamics - Fluid Mechanics - Heat Transfer - Mass Transfer - Reaction Engineering - Separation Processes - Distillation - Absorption - Extraction - Membrane Separations - Unit Operations - Aspen Plus - Aspen HYSYS - CHEMCAD - PFDs (Process Flow Diagrams) - P&IDs (Piping & Instrumentation Diagrams) - HAZOP - LOPA

Mercor

Electrical Engineering Expert

MercorEngineering

$70-$120/hr

Worldwide

Apply

About this role

The research teams behind the best-known AI models come to Mercor for electrical engineering judgment they can't generate on their own. Your standards and expertise become the rubric that frontier AI is graded against. This is a standing listing for electrical engineers who want AI training and evaluation work, not a specific job opening. It stays open whether or not a matching project is running this week. New projects start on short notice, so instead of posting and pulling a listing each time, we keep one open per field and draw from it when one begins. What the work looks like We match electrical engineers in the network to projects like: - Writing a circuit or systems problem from work you have done, with the specification, the constraints, and the operating conditions, plus the reference answer a model's attempt gets graded against - Grading model-written design and analysis: whether the topology suits the requirement, whether the noise and stability margins hold, whether the timing closes - Flagging where a model's design simulates cleanly and fails on a real board, given parasitics, tolerance stack-up, or interference Past rates have run $70 to $120 an hour, set per project by scope and depth. What we're looking for - A degree in electrical engineering, with professional design, test, or systems experience - Clear written communication, since most of the work involves explaining your reasoning - Comfort with ambiguous tasks, and willingness to flag unclear instructions Where you trained matters less than whether you have debugged your own design on the bench and found out what the simulation missed. How it works Apply here with your resume and confirm where you work from, then take a short AI interview, about 20 minutes total. We verify your background and add you to the electrical engineering pool. When a project needs electrical engineering expertise, we invite matching people from the pool to that specific listing. It names the rate, the hours, and the client, and any hiring decision is made there. What to expect This listing does not accept or reject candidates, so you will not get a decision on it. We reach out when a project matches your background. Depending on what our clients are running, that can be within a week or several months. Finishing the domain expert interview and joining every network you qualify for both improve your odds of being matched. You only need to sign up once to be eligible across all of them.

SME

Mechanical Engineer Quality Assurance Lead (QAL)

SMEEngineering / Business and Consulting

Up to $75/hr

United States

Apply

About this role

In this hourly, remote contractor role, you will work as a Mechanical Engineering Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across mechanical engineering AI training projects. You will review AI-generated mechanical engineering content and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that all contributors follow the expected quality standards. You will assess work for technical accuracy, engineering reasoning, calculation correctness, standards awareness, clarity, safety considerations, unit consistency, formatting, instruction-following, and adherence to project-specific rubrics. You will spot recurring quality issues, communicate updates to trainers and QAs, support onboarding, maintain documentation, and help activate contributors who are not working consistently. This role requires strong mechanical engineering expertise, strong English communication skills, excellent attention to detail, structured communication, and the ability to manage quality workflows across remote technical teams. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your mechanical engineering quality leadership will directly help improve the world’s premier AI models by ensuring that engineering training data is accurate, logically sound, clearly explained, well-documented, and aligned with client expectations. Selection process involves an AI interview, a domain-specific task, and an interview with a recruiter. Important: There is no immediate project for this role; however, if qualified, you will be among the first experts we reach out to when relevant opportunities arise. This will also provide you with access to future projects available through our expert network. Requirements - Bachelor’s or Master’s degree in Mechanical Engineering, Aerospace Engineering, Mechatronics, Manufacturing Engineering, or a closely related engineering field. - Strong grasp of the English language to follow project guidelines, communicate with teams, and provide clear technical feedback in English. - 3+ years of professional experience in mechanical engineering, product design, manufacturing, R&D, systems engineering, CAD, simulation, technical review, engineering education, or related workflows. - Strong understanding of core mechanical engineering topics such as mechanics, thermodynamics, fluid mechanics, heat transfer, machine design, materials, manufacturing processes, dynamics, statics, and engineering drawing interpretation. - Ability to evaluate engineering content against detailed rubrics and identify issues such as incorrect assumptions, flawed calculations, missing units, unsafe recommendations, poor reasoning, hallucinated standards, or incomplete explanations. - Familiarity with common engineering tools or workflows such as CAD, FEA/CAE, MATLAB, Python, SolidWorks, AutoCAD, ANSYS, Fusion 360, or similar tools is preferred. - Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, technical writers, or QAs is strongly preferred. - Comfortable working in fast-moving remote environments using tools such as Discord, Google Sheets, Google Docs, trackers, dashboards, and project management systems. - Highly detail-oriented and organized, with the ability to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and other quality documentation. - Experience with AI training, data annotation, large language models, prompt/response evaluation, technical content QA, or rubric-based LLM evaluation is a strong plus. Responsibilities - Quality monitoring: Spot-check mechanical engineering items, identify quality issues, provide ongoing feedback through DMs, and escalate recurring or critical issues. - Technical review: Evaluate AI-generated engineering explanations, calculations, design recommendations, diagrams/descriptions, and problem-solving steps for correctness and clarity. - Trainer and QA communication: Update trainers and QAs on Discord about new item guidelines, project changes, workflow updates, quality expectations, and engineering-specific review standards. - Question handling: Respond to trainer/QA questions clearly and promptly, especially around engineering assumptions, units, formulas, calculations, safety concerns, standards references, and rubric interpretation. - Trainer/QA activation management: DM contributors who are inactive or not working, encourage activation, track follow-ups, and flag availability issues when needed. - Documentation: Create and maintain mechanical engineering project documentation, including style guides, trackers, FAQs, quality notes, examples, honeypots, calibration tasks, and onboarding materials. - Onboarding and training: Schedule and run onboarding/training calls with trainers and QAs to explain project expectations, workflows, rubrics, quality standards, and mechanical-engineering-specific review requirements. - Quality alignment: Ensure all trainers and QAs apply engineering guidelines consistently and understand updates as projects evolve. - Risk and safety review: Flag unsafe, misleading, or overconfident engineering recommendations, especially where design, manufacturing, equipment, structural integrity, or operational safety may be affected. - Process improvement: Identify recurring quality gaps, propose workflow improvements, and help build scalable QA processes for mechanical engineering AI training projects. Skills - Mechanical Engineering - Engineering Calculations - LLM Evaluation - Design Review - Engineering QA - Technical Review - AI Training - Documentation - Trainer Feedback - English - CAD Additional skills - Quality Assurance (QA) - Mechanical Engineering - Technical Review - Rubric-Based Evaluation - Engineering Calculations Verification - Design Review - Manufacturing Processes - Materials Engineering - Machine Design - Statics - Dynamics - Thermodynamics - Fluid Mechanics - Heat Transfer - Engineering Drawings - GD&T - Root Cause Analysis - Corrective and Preventive Action (CAPA) - Failure Mode and Effects Analysis (FMEA) - ISO 9001 - Continuous Improvement - CAD - SolidWorks - AutoCAD - Fusion 360 - ANSYS - FEA/CAE - MATLAB - Python - LLM Evaluation

Mercor

Industrial & Manufacturing Engineers (Must own MacBook)

MercorEngineering / Business and Consulting

$50-$60/hr

Worldwide

Apply

SME

Mechanical Engineer

SMEEngineering

Up to $70/hr

17 countries

Apply

About this role

In this hourly, remote contractor role, you will review AI-generated engineering solutions and/or generate expert Mechanical Engineering content, evaluating reasoning quality and step-by-step problem-solving while providing crisp written feedback. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify methodological or conceptual errors; fact-check assumptions; write high-quality explanations and model solutions; and rate and compare multiple responses based on correctness and reasoning quality. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Your mechanical engineering expertise directly helps improve the world’s premier AI models by making their technical reasoning more accurate, reliable, and clearly explained. Requirements - Bachelor’s degree (or higher) in Mechanical Engineering, Aerospace Engineering, or Engineering Physics (Thermo/Heat Transfer/Fluids/Statics-Dynamics/Differential Equations). - Strong, confident fundamentals in mechanics, thermodynamics, fluid mechanics, applied physics, engineering math, and system modeling. - Comfortable evaluating technical solutions for correctness, methodology, units/dimensional consistency, assumptions, and physical plausibility with high attention to detail. - Able to clearly explain reasoning and corrections in writing; Minimum C1 English proficiency. - Experience applying basic design principles (requirements, constraints, margins, trade-offs) in real engineering contexts. - Reliable, self-directed, and able to deliver consistent quality in an hourly, remote contractor workflow across time zones. - Previous experience with AI data training/annotation or technical reviewing is strongly preferred. Responsibilities - Develop AI Training Content: Create detailed prompts in various topics and responses to guide AI learning, ensuring the models reflect a comprehensive understanding of diverse subjects. - Optimize AI Performance: Evaluate and rank AI responses to enhance the model's accuracy, fluency, and contextual relevance. - Ensure Model Integrity: Test AI models for potential inaccuracies or biases, validating their reliability across use cases. Skills - Design Principles - Mechanical Engineering - System Modeling - Statics - Dynamics - Differential Equations - English - Fluid Mechanics - Heat Transfer - Thermodynamics Additional skills - Mechanical Engineering - Thermodynamics - Heat Transfer - Fluid Mechanics - Solid Mechanics - Statics - Dynamics - Applied Physics - Engineering Mathematics - Differential Equations - System Modeling - Dimensional Analysis - Units & Measurements - Engineering Design - Requirements Engineering - Trade-off Analysis - Design Margins - Technical Review - Root Cause Analysis - Failure Analysis - Finite Element Analysis (FEA) - Computational Fluid Dynamics (CFD) - CAD (Computer-Aided Design) - SolidWorks - ANSYS - MATLAB - Python - Technical Writing - AI Data Annotation - Quality Assurance (QA)

Mercor

Civil Engineers & Architects (Must own MacBook)

MercorEngineering

$50-$60/hr

Worldwide

Apply

SME

Chemical Engineer

SMEEngineering

Up to $70/hr

UK

Apply

About this role

If you are a chemical engineer who thrives on technical precision, applied problem-solving, and real-world process reasoning, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex chemical engineering concepts. We are looking for chemical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Chemical Engineer will directly help improve the world’s premier AI models, and will play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional chemical engineering experience, with meaningful hands-on work in process design, plant/operations engineering, process safety, scale-up, manufacturing, utilities, EHS, quality, R&D, controls/automation interfaces, or a closely related chemical engineering specialty. - Deep knowledge of chemical engineering fundamentals, including material & energy balances, thermodynamics, fluid mechanics, heat & mass transfer, reaction engineering, separations (distillation, absorption, extraction, membranes), unit operations, and process control concepts. - Strong comfort with engineering calculations, assumptions, constraints, and defensible reasoning (including uncertainty, safety factors, and limitations). - Bachelor’s degree in Chemical Engineering (or closely related) required; Master’s/PhD, PE/Chartered credentials, or advanced professional certifications strongly preferred. - Previous experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with tools and artifacts such as PFDs/P&IDs, Aspen Plus/HYSYS, CHEMCAD, process datasheets, PSM documentation, HAZOP/LOPA, or SOPs is a plus. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across chemical engineering topics. - Challenge advanced language models with realistic chemical engineering scenarios, calculations, and process-informed reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step engineering solutions. - Provide structured feedback that identifies factual errors, flawed assumptions, missing constraints, unsafe recommendations, unit/consistency mistakes, or incomplete reasoning. - Assess model performance on topics such as: Material & energy balances, phase behavior, and thermodynamic property use, Unit operations and sizing logic, Distillation/separations design logic and feasibility checks, Process control reasoning, Process safety, Scale-up/manufacturability, operability, and troubleshooting of plant scenarios - Help shape AI communication standards for technical chemical engineering content, including how models explain assumptions, limitations, calculations, and professional judgment. - Ensure AI-generated content reflects sound engineering principles, appropriate safety considerations, and responsible technical communication (including “when to escalate to a licensed engineer/site expert”). Additional skills - Process Design - Plant Engineering - Process Safety Management (PSM) - Scale-Up Engineering - Manufacturing Engineering - Utilities Engineering - Environmental Health & Safety (EHS) - Quality Assurance (QA) - Research & Development (R&D) - Process Control - Controls & Automation - Material & Energy Balances - Thermodynamics - Fluid Mechanics - Heat Transfer - Mass Transfer - Reaction Engineering - Separation Processes - Distillation - Absorption - Extraction - Membrane Separations - Unit Operations - Aspen Plus - Aspen HYSYS - CHEMCAD - PFDs (Process Flow Diagrams) - P&IDs (Piping & Instrumentation Diagrams) - HAZOP - LOPA

Mercor

Electrical & Hardware Engineering Experts

MercorEngineering

$100-$120/hr

Worldwide

Apply

About this role

Mercor is seeking experienced Electrical and Hardware Engineers to support an advanced engineering and AI research initiative with a leading technology organisation. We are looking for deeply hands-on engineers who have designed, built, tested, brought up, debugged, or validated real-world hardware systems in production environments. Relevant backgrounds include: - RF / Antenna Engineering - Power Electronics Engineering - Analog / Mixed-Signal Engineering - Hardware / PCB Design Engineering - Signal Integrity Engineering This role is particularly well suited for engineers who have worked directly on complex physical products and can bring practical engineering judgment to evaluating technical designs, troubleshooting workflows, and real-world hardware problems. Key Responsibilities - Apply hands-on electrical and hardware engineering expertise to technically complex engineering tasks. - Review and evaluate hardware designs, engineering workflows, technical analyses, and troubleshooting approaches. - Analyse design trade-offs, failure modes, measurements, test results, and system-level engineering decisions. - Assess the technical correctness and practicality of engineering solutions generated for real-world hardware problems. - Identify errors, missing assumptions, unrealistic recommendations, and potential design or implementation risks. - Develop or review technically rigorous engineering problems, reference solutions, evaluation criteria, or supporting documentation. - Draw on practical experience with hardware development, validation, bring-up, debugging, manufacturing, and testing. - Provide clear technical feedback grounded in real engineering experience and industry best practices. You’re a Strong Fit If You Have - 5+ years of professional industry experience, including at least 3 years of recent, actively hands-on experience in hardware development, testing, bring-up, validation, or troubleshooting. - Direct experience serving as the responsible engineer for substantial portions of a hardware development or engineering workflow, rather than solely managing engineering teams or projects. - Deep expertise in at least one of the following areas: - RF systems, antennas, electromagnetic design, or RF validation - Power electronics, power conversion, motor drives, or power delivery - Analog or mixed-signal circuit design - PCB architecture, schematic design, board bring-up, or hardware debugging - Signal integrity, power integrity, high-speed interfaces, or system-level electrical validation - Strong understanding of practical engineering constraints including component selection, tolerances, measurement, manufacturing, reliability, thermal considerations, and system integration. - Experience debugging real hardware using relevant laboratory equipment, simulation tools, and engineering instrumentation. - Ability to explain technical decisions, trade-offs, and failure modes clearly and rigorously. Preferred Background Experience working for a company that designs and manufactures physical hardware products is strongly preferred. Relevant organisations may include, but are not limited to: - Aerospace & Defence: Lockheed Martin, Northrop Grumman, RTX, Boeing, General Atomics, L3Harris, BAE Systems, General Dynamics, Honeywell Aerospace, Textron - Space: Blue Origin, Rocket Lab, Relativity Space, Firefly Aerospace, Sierra Space, Astranis, Planet, Maxar, Axiom Space - Automotive & EV: Tesla, Rivian, General Motors, Ford, Lucid, Waymo, Zoox, Aptiv, Bosch - Semiconductors: NVIDIA, Qualcomm, Intel, Analogue Devices, Texas Instruments, Broadcom, Marvell, Micron, NXP, Infineon - Consumer Electronics & Computing: Apple, Google Hardware, Meta Reality Labs, Microsoft Devices, Amazon, Samsung, Garmin, Sonos - Drones, eVTOL & Robotics: Skydio, Shield AI, Zipline, Joby Aviation, Archer Aviation, Boston Dynamics, Figure, Agility Robotics, Wing - Industrial, Energy & Medical Devices: Siemens, GE Aerospace, GE Vernova, ABB, Schneider Electric, Rockwell Automation, Enphase, Medtronic, Intuitive Surgical Candidates from comparable hardware-focused organisations are equally encouraged to apply. Why Join - Apply your engineering expertise to technically challenging problems at the intersection of advanced hardware engineering and AI research. - Work on projects where practical, real-world engineering experience is highly valued. - Help improve how advanced AI systems reason about electrical engineering, hardware design, testing, and troubleshooting. - Contribute remotely with flexible engagement structures alongside experienced engineers and researchers. - Work on problems that require genuine engineering judgment rather than purely theoretical knowledge.

SME

Biomedical Engineer

SMEEngineering

Up to $70/hr

UK

Apply

About this role

If you are a biomedical engineer who thrives on technical precision, applied problem-solving, and rigorous engineering reasoning in health and life-science contexts, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex biomedical engineering concepts. We are looking for biomedical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Biomedical Engineer will directly help improve the world’s premier AI models—and play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional biomedical engineering experience, with significant hands-on work in one or more areas such as medical devices, biomechanics, biomaterials, tissue engineering, bioinstrumentation, imaging systems, signals & systems (physiologic), rehabilitation engineering, clinical engineering, quality/regulatory, manufacturing/validation, or a closely related specialty. - Deep knowledge of biomedical engineering fundamentals, such as physiology for engineers, transport phenomena in biological systems, biomechanics, materials behavior in biological environments, biosignals, sensor/measurement systems, and systems modeling (depending on specialty). - Strong comfort with technical assumptions, constraints, unit consistency, and defensible reasoning (including limitations, uncertainty, and safety considerations). - Bachelor’s degree in Biomedical Engineering (or closely related) required; Master’s/PhD or advanced credentials strongly preferred. - Experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with any of the following is a plus (not required): ISO 13485, IEC 60601, ISO 14971, FDA design controls (21 CFR 820), verification & validation, risk management, biocompatibility concepts (ISO 10993), or clinical workflow constraints. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across biomedical engineering topics. - Challenge advanced language models with realistic biomedical engineering scenarios, calculations, and design/analysis reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step solutions (including unit handling and correct interpretation of constraints). - Provide structured feedback that identifies factual errors, unsafe recommendations, unsupported clinical claims, missing assumptions, invalid simplifications, misuse of standards, or incomplete reasoning. - Assess model performance on topics such as: Biomechanics, Bioinstrumentation & sensors, Biomedical signals, Medical device design, Biomaterials, Imaging & measurement, Verification/validation & risk - Help shape AI communication standards for biomedical content, including how models explain assumptions, risk/limitations, what must be verified experimentally, and when to escalate to clinical/regulatory experts. - Ensure AI-generated content reflects responsible biomedical engineering practice—especially around patient safety, clinical claims, and regulatory-sensitive topics. Additional skills - Medical Device Design - Biomechanics - Biomaterials - Tissue Engineering - Bioinstrumentation - Physiological Signal Processing - Signals & Systems - Medical Imaging Systems - Rehabilitation Engineering - Clinical Engineering - Physiology - Transport Phenomena - Systems Modeling - Sensor Design - Data Acquisition (DAQ) - MATLAB - Python - LabVIEW - SolidWorks - Finite Element Analysis (FEA) - Design of Experiments (DoE) - Verification & Validation (V&V) - Risk Management (ISO 14971) - ISO 13485 - IEC 60601 - FDA Design Controls (21 CFR 820) - Biocompatibility (ISO 10993) - Quality Management Systems (QMS) - Manufacturing Validation - AI Data Annotation

SME

Civil Engineer

SMEEngineering

Up to $60/hr

Brazil

Apply

About this role

If you are a civil engineer who thrives on technical precision, applied problem-solving, and infrastructure-focused reasoning, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex engineering concepts. We are looking for civil engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Civil Engineer will directly help improve the world’s premier AI models, and will play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional civil engineering experience, with significant hands-on work in infrastructure design, structural analysis, geotechnical engineering, transportation engineering, water resources, environmental engineering, construction management, or a closely related civil engineering specialty. - Deep knowledge of civil engineering fundamentals, including statics, mechanics of materials, soil mechanics, hydraulics, materials behavior, load paths, construction methods, and infrastructure systems. - Bachelor’s degree in Civil Engineering or a closely related engineering discipline required; Master’s degree, PhD, PE licensure, or equivalent advanced professional credentials strongly preferred. - Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across civil engineering topics. - Challenge advanced language models with realistic civil engineering scenarios, calculations, design questions, and code-informed reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step engineering solutions. - Provide structured feedback that identifies factual errors, flawed assumptions, missing constraints, unsafe recommendations, or incomplete reasoning. - Assess model performance on topics such as structural loads, soil behavior, slope stability, drainage design, pavement systems, reinforced concrete, steel design, and construction sequencing. - Help shape AI communication standards for technical civil engineering content, including how models explain assumptions, limitations, calculations, and professional judgment. - Ensure AI-generated content reflects sound engineering principles, appropriate safety considerations, and responsible technical communication. Additional skills - Civil Engineering - Infrastructure Design - Structural Analysis - Geotechnical Engineering - Transportation Engineering - Water Resources Engineering - Environmental Engineering - Construction Management - Site Development - Roadway Design - Stormwater Management - Hydraulic Modeling - Hydrology - Pavement Design - Traffic Engineering - Soil Mechanics - Foundation Design - Earthworks - Slope Stability - Retaining Wall Design - Concrete Design - Steel Design - Reinforced Concrete - Construction Materials - Load Calculations - AutoCAD Civil 3D - MicroStation - HEC-RAS - EPA SWMM - Project Management - PE License

SME

Electrical Engineer

SMEEngineering

Up to $60/hr

Brazil

Apply

About this role

If you are an electrical engineer who thrives on technical precision, applied problem-solving, and rigorous reasoning across circuits, power, and systems, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex electrical engineering concepts. We are looking for electrical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as an Electrical Engineer will directly help improve the world’s premier AI models—and play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional electrical engineering experience, with significant hands-on work in one or more areas such as power systems, power electronics, industrial controls, embedded systems, analog/digital circuit design, RF/communications, signal processing, instrumentation, automation, electronics manufacturing/test, or a closely related specialty. - Deep knowledge of electrical engineering fundamentals, including circuit analysis, electronics, electromagnetics, signals & systems, control fundamentals, and safe engineering practices (grounding, isolation, protection, EMC/EMI). - Strong comfort with engineering calculations, assumptions, constraints, unit consistency, and defensible reasoning (including limitations and safety considerations). - Bachelor’s degree in Electrical Engineering (or closely related) required; Master’s/PhD, PE/Chartered, or advanced professional certifications strongly preferred. - Previous experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with tools/artifacts such as schematics, SPICE simulation, MATLAB/Simulink, PCB design, oscilloscopes/logic analyzers, power studies, or test reports is a plus. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across electrical engineering topics. - Challenge advanced language models with realistic electrical engineering scenarios, calculations, and standards-informed reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step solutions (including correct math, units, and assumptions). - Provide structured feedback that identifies factual errors, unsafe recommendations, missing constraints, invalid assumptions, incorrect modeling, or incomplete reasoning. - Assess model performance on topics such as: Circuit design/analysis, Power systems, Power electronics, Controls, Embedded & digital, EMI/EMC & safety, Test & troubleshooting - Help shape AI communication standards for technical EE content, including how models explain assumptions, limits, safety concerns, and professional judgment. - Ensure AI-generated content reflects responsible engineering practice—especially around electrical safety, compliance, and real-world feasibility. Additional skills - Power Systems - Power Electronics - Circuit Analysis - Analog Circuit Design - Digital Circuit Design - Embedded Systems - Industrial Controls - Automation - Instrumentation - Control Systems - Signals & Systems - Electromagnetics - RF Engineering - Communications Systems - Signal Processing - PCB Design - Schematic Capture - SPICE Simulation - MATLAB - Simulink - Oscilloscope - Logic Analyzer - EMC/EMI Compliance - Grounding & Bonding - Electrical Safety - Protection Systems - Power System Studies - Electronics Testing - Electronics Manufacturing - PE License

SME

Chemical Engineer

SMEEngineering

Up to $60/hr

+1

Apply

About this role

If you are a chemical engineer who thrives on technical precision, applied problem-solving, and real-world process reasoning, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex chemical engineering concepts. We are looking for chemical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Chemical Engineer will directly help improve the world’s premier AI models, and will play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional chemical engineering experience, with meaningful hands-on work in process design, plant/operations engineering, process safety, scale-up, manufacturing, utilities, EHS, quality, R&D, controls/automation interfaces, or a closely related chemical engineering specialty. - Deep knowledge of chemical engineering fundamentals, including material & energy balances, thermodynamics, fluid mechanics, heat & mass transfer, reaction engineering, separations (distillation, absorption, extraction, membranes), unit operations, and process control concepts. - Strong comfort with engineering calculations, assumptions, constraints, and defensible reasoning (including uncertainty, safety factors, and limitations). - Bachelor’s degree in Chemical Engineering (or closely related) required; Master’s/PhD, PE/Chartered credentials, or advanced professional certifications strongly preferred. - Previous experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with tools and artifacts such as PFDs/P&IDs, Aspen Plus/HYSYS, CHEMCAD, process datasheets, PSM documentation, HAZOP/LOPA, or SOPs is a plus. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across chemical engineering topics. - Challenge advanced language models with realistic chemical engineering scenarios, calculations, and process-informed reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step engineering solutions. - Provide structured feedback that identifies factual errors, flawed assumptions, missing constraints, unsafe recommendations, unit/consistency mistakes, or incomplete reasoning. - Assess model performance on topics such as: Material & energy balances, phase behavior, and thermodynamic property use, Unit operations and sizing logic, Distillation/separations design logic and feasibility checks, Process control reasoning, Process safety, Scale-up/manufacturability, operability, and troubleshooting of plant scenarios - Help shape AI communication standards for technical chemical engineering content, including how models explain assumptions, limitations, calculations, and professional judgment. - Ensure AI-generated content reflects sound engineering principles, appropriate safety considerations, and responsible technical communication (including “when to escalate to a licensed engineer/site expert”). Additional skills - Process Design - Plant Engineering - Process Safety Management (PSM) - Scale-Up Engineering - Manufacturing Engineering - Utilities Engineering - Environmental Health & Safety (EHS) - Quality Assurance (QA) - Research & Development (R&D) - Process Control - Controls & Automation - Material & Energy Balances - Thermodynamics - Fluid Mechanics - Heat Transfer - Mass Transfer - Reaction Engineering - Separation Processes - Distillation - Absorption - Extraction - Membrane Separations - Unit Operations - Aspen Plus - Aspen HYSYS - CHEMCAD - PFDs (Process Flow Diagrams) - P&IDs (Piping & Instrumentation Diagrams) - HAZOP - LOPA

SME

Biomedical Engineer

SMEEngineering

Up to $60/hr

+1

Apply

About this role

If you are a biomedical engineer who thrives on technical precision, applied problem-solving, and rigorous engineering reasoning in health and life-science contexts, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex biomedical engineering concepts. We are looking for biomedical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Biomedical Engineer will directly help improve the world’s premier AI models—and play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional biomedical engineering experience, with significant hands-on work in one or more areas such as medical devices, biomechanics, biomaterials, tissue engineering, bioinstrumentation, imaging systems, signals & systems (physiologic), rehabilitation engineering, clinical engineering, quality/regulatory, manufacturing/validation, or a closely related specialty. - Deep knowledge of biomedical engineering fundamentals, such as physiology for engineers, transport phenomena in biological systems, biomechanics, materials behavior in biological environments, biosignals, sensor/measurement systems, and systems modeling (depending on specialty). - Strong comfort with technical assumptions, constraints, unit consistency, and defensible reasoning (including limitations, uncertainty, and safety considerations). - Bachelor’s degree in Biomedical Engineering (or closely related) required; Master’s/PhD or advanced credentials strongly preferred. - Experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with any of the following is a plus (not required): ISO 13485, IEC 60601, ISO 14971, FDA design controls (21 CFR 820), verification & validation, risk management, biocompatibility concepts (ISO 10993), or clinical workflow constraints. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across biomedical engineering topics. - Challenge advanced language models with realistic biomedical engineering scenarios, calculations, and design/analysis reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step solutions (including unit handling and correct interpretation of constraints). - Provide structured feedback that identifies factual errors, unsafe recommendations, unsupported clinical claims, missing assumptions, invalid simplifications, misuse of standards, or incomplete reasoning. - Assess model performance on topics such as: Biomechanics, Bioinstrumentation & sensors, Biomedical signals, Medical device design, Biomaterials, Imaging & measurement, Verification/validation & risk - Help shape AI communication standards for biomedical content, including how models explain assumptions, risk/limitations, what must be verified experimentally, and when to escalate to clinical/regulatory experts. - Ensure AI-generated content reflects responsible biomedical engineering practice—especially around patient safety, clinical claims, and regulatory-sensitive topics. Additional skills - Medical Device Design - Biomechanics - Biomaterials - Tissue Engineering - Bioinstrumentation - Physiological Signal Processing - Signals & Systems - Medical Imaging Systems - Rehabilitation Engineering - Clinical Engineering - Physiology - Transport Phenomena - Systems Modeling - Sensor Design - Data Acquisition (DAQ) - MATLAB - Python - LabVIEW - SolidWorks - Finite Element Analysis (FEA) - Design of Experiments (DoE) - Verification & Validation (V&V) - Risk Management (ISO 14971) - ISO 13485 - IEC 60601 - FDA Design Controls (21 CFR 820) - Biocompatibility (ISO 10993) - Quality Management Systems (QMS) - Manufacturing Validation - AI Data Annotation

SME

Civil Engineer

SMEEngineering

Up to $45/hr

14 countries

Apply

About this role

If you are a civil engineer who thrives on technical precision, applied problem-solving, and infrastructure-focused reasoning, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex engineering concepts. We are looking for civil engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Civil Engineer will directly help improve the world’s premier AI models, and will play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional civil engineering experience, with significant hands-on work in infrastructure design, structural analysis, geotechnical engineering, transportation engineering, water resources, environmental engineering, construction management, or a closely related civil engineering specialty. - Deep knowledge of civil engineering fundamentals, including statics, mechanics of materials, soil mechanics, hydraulics, materials behavior, load paths, construction methods, and infrastructure systems. - Bachelor’s degree in Civil Engineering or a closely related engineering discipline required; Master’s degree, PhD, PE licensure, or equivalent advanced professional credentials strongly preferred. - Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across civil engineering topics. - Challenge advanced language models with realistic civil engineering scenarios, calculations, design questions, and code-informed reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step engineering solutions. - Provide structured feedback that identifies factual errors, flawed assumptions, missing constraints, unsafe recommendations, or incomplete reasoning. - Assess model performance on topics such as structural loads, soil behavior, slope stability, drainage design, pavement systems, reinforced concrete, steel design, and construction sequencing. - Help shape AI communication standards for technical civil engineering content, including how models explain assumptions, limitations, calculations, and professional judgment. - Ensure AI-generated content reflects sound engineering principles, appropriate safety considerations, and responsible technical communication. Additional skills - Civil Engineering - Infrastructure Design - Structural Analysis - Geotechnical Engineering - Transportation Engineering - Water Resources Engineering - Environmental Engineering - Construction Management - Site Development - Roadway Design - Stormwater Management - Hydraulic Modeling - Hydrology - Pavement Design - Traffic Engineering - Soil Mechanics - Foundation Design - Earthworks - Slope Stability - Retaining Wall Design - Concrete Design - Steel Design - Reinforced Concrete - Construction Materials - Load Calculations - AutoCAD Civil 3D - MicroStation - HEC-RAS - EPA SWMM - Project Management - PE License

SME

Electrical Engineer

SMEEngineering

Up to $40/hr

14 countries

Apply

About this role

If you are an electrical engineer who thrives on technical precision, applied problem-solving, and rigorous reasoning across circuits, power, and systems, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex electrical engineering concepts. We are looking for electrical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as an Electrical Engineer will directly help improve the world’s premier AI models—and play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional electrical engineering experience, with significant hands-on work in one or more areas such as power systems, power electronics, industrial controls, embedded systems, analog/digital circuit design, RF/communications, signal processing, instrumentation, automation, electronics manufacturing/test, or a closely related specialty. - Deep knowledge of electrical engineering fundamentals, including circuit analysis, electronics, electromagnetics, signals & systems, control fundamentals, and safe engineering practices (grounding, isolation, protection, EMC/EMI). - Strong comfort with engineering calculations, assumptions, constraints, unit consistency, and defensible reasoning (including limitations and safety considerations). - Bachelor’s degree in Electrical Engineering (or closely related) required; Master’s/PhD, PE/Chartered, or advanced professional certifications strongly preferred. - Previous experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with tools/artifacts such as schematics, SPICE simulation, MATLAB/Simulink, PCB design, oscilloscopes/logic analyzers, power studies, or test reports is a plus. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across electrical engineering topics. - Challenge advanced language models with realistic electrical engineering scenarios, calculations, and standards-informed reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step solutions (including correct math, units, and assumptions). - Provide structured feedback that identifies factual errors, unsafe recommendations, missing constraints, invalid assumptions, incorrect modeling, or incomplete reasoning. - Assess model performance on topics such as: Circuit design/analysis, Power systems, Power electronics, Controls, Embedded & digital, EMI/EMC & safety, Test & troubleshooting - Help shape AI communication standards for technical EE content, including how models explain assumptions, limits, safety concerns, and professional judgment. - Ensure AI-generated content reflects responsible engineering practice—especially around electrical safety, compliance, and real-world feasibility. Additional skills - Power Systems - Power Electronics - Circuit Analysis - Analog Circuit Design - Digital Circuit Design - Embedded Systems - Industrial Controls - Automation - Instrumentation - Control Systems - Signals & Systems - Electromagnetics - RF Engineering - Communications Systems - Signal Processing - PCB Design - Schematic Capture - SPICE Simulation - MATLAB - Simulink - Oscilloscope - Logic Analyzer - EMC/EMI Compliance - Grounding & Bonding - Electrical Safety - Protection Systems - Power System Studies - Electronics Testing - Electronics Manufacturing - PE License

SME

Biomedical Engineer

SMEEngineering

Up to $40/hr

14 countries

Apply

About this role

If you are a biomedical engineer who thrives on technical precision, applied problem-solving, and rigorous engineering reasoning in health and life-science contexts, this is a unique opportunity to contribute directly to how the next generation of AI systems understand and communicate complex biomedical engineering concepts. We are looking for biomedical engineering specialists who can evaluate, challenge, and refine advanced language models on domain-specific topics. Your expertise as a Biomedical Engineer will directly help improve the world’s premier AI models—and play an important role in shaping the future of AI. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate, delivering training data for many of the world’s largest AI companies and foundation-model labs. Requirements - 4+ years of professional biomedical engineering experience, with significant hands-on work in one or more areas such as medical devices, biomechanics, biomaterials, tissue engineering, bioinstrumentation, imaging systems, signals & systems (physiologic), rehabilitation engineering, clinical engineering, quality/regulatory, manufacturing/validation, or a closely related specialty. - Deep knowledge of biomedical engineering fundamentals, such as physiology for engineers, transport phenomena in biological systems, biomechanics, materials behavior in biological environments, biosignals, sensor/measurement systems, and systems modeling (depending on specialty). - Strong comfort with technical assumptions, constraints, unit consistency, and defensible reasoning (including limitations, uncertainty, and safety considerations). - Bachelor’s degree in Biomedical Engineering (or closely related) required; Master’s/PhD or advanced credentials strongly preferred. - Experience with AI data training, annotation, red-teaming, or evaluating AI-generated technical content is a strong plus. - Familiarity with any of the following is a plus (not required): ISO 13485, IEC 60601, ISO 14971, FDA design controls (21 CFR 820), verification & validation, risk management, biocompatibility concepts (ISO 10993), or clinical workflow constraints. Responsibilities - Evaluate AI-generated responses for technical accuracy, logical soundness, completeness, and clarity across biomedical engineering topics. - Challenge advanced language models with realistic biomedical engineering scenarios, calculations, and design/analysis reasoning tasks. - Review and refine AI-generated prompts, model responses, explanations, and step-by-step solutions (including unit handling and correct interpretation of constraints). - Provide structured feedback that identifies factual errors, unsafe recommendations, unsupported clinical claims, missing assumptions, invalid simplifications, misuse of standards, or incomplete reasoning. - Assess model performance on topics such as: Biomechanics, Bioinstrumentation & sensors, Biomedical signals, Medical device design, Biomaterials, Imaging & measurement, Verification/validation & risk - Help shape AI communication standards for biomedical content, including how models explain assumptions, risk/limitations, what must be verified experimentally, and when to escalate to clinical/regulatory experts. - Ensure AI-generated content reflects responsible biomedical engineering practice—especially around patient safety, clinical claims, and regulatory-sensitive topics. Additional skills - Medical Device Design - Biomechanics - Biomaterials - Tissue Engineering - Bioinstrumentation - Physiological Signal Processing - Signals & Systems - Medical Imaging Systems - Rehabilitation Engineering - Clinical Engineering - Physiology - Transport Phenomena - Systems Modeling - Sensor Design - Data Acquisition (DAQ) - MATLAB - Python - LabVIEW - SolidWorks - Finite Element Analysis (FEA) - Design of Experiments (DoE) - Verification & Validation (V&V) - Risk Management (ISO 14971) - ISO 13485 - IEC 60601 - FDA Design Controls (21 CFR 820) - Biocompatibility (ISO 10993) - Quality Management Systems (QMS) - Manufacturing Validation - AI Data Annotation

Engineering AI training jobs. Earn on your schedule.

Browse by field

Platforms

Get this week’s AI training jobs

Filters

Job listings41

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role

About this role