Software, AI and Data AI Training Jobs - Compare Pay

micro1

2D Game Developer (Defold)

micro1Software, AI and Data4 days ago

$70-$130/hr

Worldwide

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SME

React and Next.js Engineer

SMESoftware, AI and Data

Up to $90/hr

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About this role

As a React / Next.js Engineer, you will work remotely on an hourly paid basis to review AI-generated React/Next.js code, frontend architectures, and technical explanations, as well as produce high-quality reference implementations and step-by-step reasoning for complex engineering problems. You will assess solutions for correctness, clarity, accessibility, security, performance, and adherence to the prompt; identify issues in React rendering behavior, state management, SSR/SSG/ISR, routing/data fetching, hydration, caching, and bundle performance; fact-check technical information; write high-quality explanations and model solutions that demonstrate best practices; and rate and compare multiple AI responses based on correctness and reasoning quality. This fully remote, hourly paid contractor role is with SME Careers, a fast-growing AI data services company and subsidiary of SuperAnnotate that provides AI training data to many of the world’s largest AI companies and foundation model labs—where your frontend expertise will directly help improve the world’s premier AI models used by millions of developers worldwide. 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 degree or higher in Computer Science, Software Engineering, or a closely related technical field (or equivalent practical experience). - 4+ years of professional experience building production web applications with React, including at least 2+ years with Next.js (or equivalent SSR framework experience). - Expert-level proficiency in modern React: hooks, component patterns, state management, memoization, rendering behavior, and testing. - Strong Next.js fundamentals (Next 13/14+ preferred): App Router, Server Components (where applicable), route handlers, middleware, caching, and deployment patterns. - Strong understanding of web fundamentals: HTTP, browser rendering, security basics (XSS/CSRF), cookies/sessions, and OAuth flows. - Performance mindset: bundle optimization, code splitting, image optimization, Core Web Vitals, and profiling. - Experience with testing and quality: Jest/Vitest, React Testing Library, Playwright/Cypress, linting, CI/CD. - Minimum C1 English proficiency (written and spoken), with the ability to write clear technical explanations and follow detailed English-language guidelines. - Proven experience conducting detailed code reviews and enforcing coding standards for maintainability, correctness, and accessibility. - Previous experience with AI data training, annotation, or evaluating AI-generated technical content is a strong plus. - Highly detail-oriented and systematic, with a methodical approach to evaluating reasoning quality and identifying subtle issues in complex UI code. Responsibilities - Develop AI Training Content: Create detailed prompts across React/Next.js topics and write high-quality reference answers to guide AI learning. - Optimize AI Performance: Evaluate and rank AI responses to enhance correctness, clarity, accessibility, and performance. - Ensure Model Integrity: Test AI models for inaccuracies or unsafe recommendations, validating reliability across real-world use cases. Skills - Code Review - Accessibility - Accessibility (WCAG) - React - Performance Optimization - Frontend Architecture - TypeScript - WCAG - SSR/SSG/ISR - Next.js - English - Debugging Additional skills - React - Next.js - JavaScript - TypeScript - HTML5 - CSS3 - Node.js - React Hooks - Server-Side Rendering (SSR) - Static Site Generation (SSG) - Next.js App Router - React Server Components - REST APIs - GraphQL - HTTP - OAuth 2.0 - Web Security (XSS/CSRF) - State Management (Redux/Zustand) - Jest - Vitest - React Testing Library - Playwright - Cypress - CI/CD - Git - ESLint - Prettier - Web Performance Optimization - Core Web Vitals - Accessibility (a11y) - Code Reviews

Mercor

Data Scientist Talent Network

MercorSoftware, AI and Data

$100-$150/hr

Worldwide

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DataAnnotation

Electrical Engineer

DataAnnotationEngineering / Software, AI and Data

Up to $40–$125+ / hour

Worldwide

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About this role

Overview DataAnnotation is looking for an experienced Electrical Engineer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring the judgment you have already built over years of designing, debugging, and shipping hardware. We bring engineering problems the models cannot yet solve on their own. This is a new and growing area for our company, focused on teaching AI to reason correctly about circuits, systems, and physical constraints. Your engineering judgment, your standard for what counts as a correct answer, and the written rationale behind them become the signal that shapes the next generation of engineering tools. What you’ll actually do - Design challenging, realistic engineering problems from your own practice: a circuit to specify, a control loop to stabilize, a power stage to size. - Run those problems through frontier AI models and judge the output against your professional standard. - Compare two model versions on identical prompts and call which performed better, and where each fell short. - Critique model-generated derivations, schematics, component selections, and calculations, and write the reasoning behind your call. - Flag concrete failures with evidence: wrong assumptions, sign and unit errors, unphysical results, invalid topologies, fabricated datasheet values, or off-brief interpretation. Problems draw on whatever you know best: - Analog, RF, and mixed-signal circuits. - Electromagnetics and antennas. - Control and systems. - Devices and materials. - Signal processing and photonics. - Power and energy systems. Roles this fits Common backgrounds: Electrical Engineer, Power Engineer, Systems Engineer. What we look for - Fluency in English (native or bilingual level). - 2+ years of industry experience in circuit or electronics engineering. - Background in electrical engineering, electronics engineering, or a closely related discipline. - Strong command of circuit analysis and design tradeoffs, and the ability to defend component-level and system-level decisions. - The ability to articulate why an answer is wrong, not only that it is. - Working comfort with AI tools, or the ability to pick them up quickly. - A current, in-progress, or completed Bachelor’s is preferred but not required. - Only applicants based in Australia, Canada, Ireland, New Zealand, the United Kingdom, or the United States will be considered for this role. How it works Apply Qualify Work & get paid Compensation Up to $125+/hr depending on task difficulty and specialization. Many contributors add $100k–$200k a year; some make it their full-time income. About DataAnnotation DataAnnotation is where 1M+ experts train the world’s leading AI models. Hundreds of millions paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.

micro1

Computational Biology & Bioinformatics Expert (PhD)

micro1Life Sciences / Software, AI and Data

$45-$90/hr

Worldwide

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About this role

Job Title: Computational Biology & Bioinformatics Expert (PhD) Job Type: Contractor Location: Remote (Worldwide) Job Summary: In this role, you’ll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. Key Responsibilities: 1. Design, evaluate, and critique bioinformatics and computational biology workflows to support AI benchmarking initiatives. 2. Provide expert-level insights on genomic, transcriptomic, and proteomic data analysis pipelines. 3. Assess and optimize pipeline parameters, tool configurations, and statistical methods for accuracy and reproducibility. 4. Analyze biological datasets (e.g., NGS, RNA-seq, variant calling, protein structure) and provide actionable recommendations. 5. Leverage domain knowledge to guide the development and validation of biology-related AI models and tools. 6. Communicate complex scientific concepts clearly, both in writing and verbally, to technical and non-technical collaborators. 7. Document findings, methodologies, and best practices to ensure knowledge transfer across the customer’s team. Required Skills and Qualifications: 1. PhD in bioinformatics, computational biology, genomics, or a closely related field, or equivalent industry/research experience. 2. Professional written and spoken English (C1 or higher). 3. Hands-on experience analyzing biological data (e.g., NGS, RNA-seq, variant analysis). 4. Proficiency in Python and/or R for scientific analysis, plus experience with standard bioinformatics tools (e.g., BLAST, samtools, GATK, Bioconductor, Biopython). 5. Experience building reproducible workflows with tools such as Nextflow or Snakemake, and comfort working in Linux/command-line environments. 6. Strong statistical, quantitative, and analytical reasoning skills. 7. Outstanding written and verbal communication abilities, with the ability to clearly document and explain technical concepts. 8. Track record of rigorous scientific problem-solving in complex biological domains. Preferred Qualifications: 1. Experience with AI/ML-assisted biology workflows or benchmarking. 2. Peer-reviewed publications, patents, or contributions to open-source bioinformatics software. 3. Background in single-cell analysis, structural biology, proteomics, or drug discovery. 4. prediction/retrosynthesis.

SME

HTML/CSS Team Lead

SMESoftware, AI and Data / Business and Consulting / Design & Creative

Up to $80/hr

United States

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About this role

In this hourly, remote contractor role, you will work as an HTML/CSS Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across HTML/CSS AI training projects. You will review AI-generated HTML/CSS code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards. You will assess work for semantic correctness, visual layout logic, accessibility, responsive design, browser compatibility, CSS architecture, maintainability, performance, formatting, instruction-following, and adherence to project-specific rubrics. This role requires strong frontend markup and styling expertise, English communication skills, excellent attention to detail, 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 HTML/CSS quality leadership will help ensure frontend training data is accurate, accessible, responsive, clearly explained, 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 Computer Science, Web Development, UX/UI, Information Technology, or equivalent professional frontend development experience. - Strong grasp of English to follow guidelines, communicate with teams, and provide clear technical feedback. - 3+ years of professional experience in HTML/CSS, frontend development, web accessibility, responsive design, UI implementation, code review, QA, or technical mentoring. - Strong understanding of semantic HTML, forms, tables, ARIA basics, accessibility, CSS selectors, cascade/specificity, box model, flexbox, grid, positioning, responsive layouts, media queries, animations, and modern CSS features. - Ability to evaluate HTML/CSS content against detailed rubrics and identify issues such as invalid markup, inaccessible components, poor responsiveness, layout bugs, overcomplicated CSS, specificity problems, browser compatibility issues, or incomplete explanations. - Familiarity with tools and workflows such as browser DevTools, Lighthouse, WCAG basics, Sass, Tailwind CSS, Bootstrap, CSS modules, design systems, Figma handoff, GitHub, CI/CD, and frontend build tools is preferred. - Experience leading or supporting remote teams of trainers, annotators, reviewers, frontend engineers, designers, coding mentors, or QAs is strongly preferred. - Comfortable working in fast-moving remote environments using Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems. - Highly organized and able to maintain style guides, trackers, FAQs, onboarding materials, honeypots, calibration tasks, and quality documentation. - Experience with AI training, data annotation, LLM evaluation, frontend code QA, accessibility review, or rubric-based code review is a strong plus. Responsibilities - Quality monitoring: Spot-check HTML/CSS items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues. - Code review: Evaluate AI-generated HTML/CSS snippets, layout implementations, accessibility fixes, responsive design solutions, debugging responses, and explanations for correctness and clarity. - Trainer and QA communication: Update contributors on Discord about guideline changes, workflow updates, and HTML/CSS-specific review standards. - Question handling: Respond to questions around semantic HTML, accessibility, ARIA, CSS specificity, layout behavior, flexbox/grid, responsive design, browser compatibility, and rubric interpretation. - Trainer/QA activation management: DM inactive contributors, encourage activation, track follow-ups, and flag availability issues. - Documentation: Create and maintain HTML/CSS style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials. - Onboarding and training: Run onboarding/training calls for HTML/CSS contributors. - Risk and accessibility review: Flag inaccessible, misleading, invalid, brittle, or non-production-ready frontend recommendations. - Process improvement: Identify recurring quality gaps and build scalable QA processes. Skills - LLM Evaluation - Code Review - Accessibility - HTML - Responsive Design - Frontend QA - AI Training - Trainer Feedback - Web Standards - CSS Additional skills - HTML5 - CSS3 - Semantic HTML - Web Accessibility (a11y) - WCAG - ARIA - Responsive Web Design - CSS Flexbox - CSS Grid - CSS Animations - CSS Specificity - Cross-Browser Compatibility - Sass/SCSS - Tailwind CSS - Bootstrap - CSS Modules - Design Systems - Figma - UI Implementation - Frontend Development - Browser DevTools - Lighthouse - Git - GitHub - CI/CD - Code Review - Quality Assurance (QA) - Technical Mentoring - Team Leadership - Technical Documentation

micro1

Quantitative Rates Researcher

micro1Finance / Software, AI and Data

$80-$150/hr

Worldwide

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About this role

micro1 is engaging Quantitative Rates Researchers to contribute to a leading investment bank’s algorithmic trading platform project. In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required — your domain knowledge is what matters. Scope of Work 1. Review and assess AI-generated quantitative research and trading strategy outputs focused on fixed income and rates markets 2. Identify and document methodological issues such as lookahead bias, overfitting, data snooping, and unrealistic transaction cost assumptions 3. Evaluate the accuracy of backtesting frameworks, especially with respect to rates-specific mechanics like carry/roll-down and contract roll conventions 4. Scrutinize the statistical rigor of signal construction, factor modeling, and alpha research in the provided outputs 5. Deliver detailed written feedback on model assumptions, implementation fidelity, and research soundness 6. Collaborate asynchronously with project coordinators by clarifying findings and suggestions through clear written and verbal communication 7. Contribute to the refinement of research evaluation processes for greater accuracy and relevance Preferred Qualifications 1. Background as a quantitative researcher, analyst, or consultant with expertise in fixed income or rates markets 2. Demonstrated experience building and backtesting systematic rates strategies at a hedge fund, asset manager, or bank 3. Advanced proficiency in Python (pandas, numpy, scipy) or R for quantitative research and data analysis 4. Strong understanding of yield curve modeling, carry/roll-down analytics, relative value trading, SOFR/Eurodollar instruments, and Treasury futures 5. Comfort evaluating research under real-world trading conditions, including transaction costs and liquidity constraints 6. Exceptional attention to detail and ability to articulate complex quantitative findings in clear, concise written feedback 7. Prior experience assessing or reviewing models for compliance with best practices in quantitative finance is a plus

Mercor

Office & Productivity Software Expert

MercorSoftware, AI and Data

$60-$70/hr

Worldwide

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About this role

The research teams behind the best-known AI models come to Mercor for judgment about how office and productivity software is actually used. Your standards and expertise become the rubric that frontier AI is graded against. This is a standing listing for people who work in these tools all day and 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 people in this network to projects like: - Writing a realistic task from your own work, a document, a model, or a deck, with the starting material and the constraint, plus the reference answer a model's attempt gets graded against - Grading model-generated documents, spreadsheets, and slides: whether the formula is correct and robust, whether the formatting survives editing, whether the deck actually makes its argument - Flagging where a model's output opens cleanly and would break in real use, given file conversion, version compatibility, or what happens once someone else edits it Listings in this field on Mercor have posted at $60 to $70 an hour, set per project by scope and depth. What we're looking for - Professional experience working at a high level in office and productivity tools - Clear written communication, since most of the work involves explaining your reasoning - Comfort with ambiguous tasks, and willingness to flag unclear instructions What this covers This pool spans office and productivity software, including: - Documents and word processing - Spreadsheets and modeling - Presentations and slides - PDF and document conversion - Email and collaboration tools - Office scripting and add-ins Depth in one tool matters more than passing familiarity with all of them. 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 office and productivity software pool. When a project needs your tool or specialty, 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.

micro1

Associate Forward Deployed Engineer (aFDE)

micro1Software, AI and Data

$40-$60/hr

Worldwide

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About this role

Job Title: Associate Forward Deployed Engineer (aFDE) Job Type: Full-time Location: Remote Work Arrangement: Hourly, with expected weekly hours agreed upfront The Role We’re hiring junior engineers to help scale data ingestion and customer data workflows. You’ll work alongside core FDEs to prepare and transfer data, troubleshoot issues, build scripts and automations, and keep customers informed. You’ll start with clearly scoped responsibilities and receive guidance as you take on more technical ownership. The initial work will combine hands-on engineering with operational execution, with the opportunity to grow into a full FDE role over time. What You’ll Do 1. Help customers bring their data into the platform, from initial preparation through successful transfer and validation. 2. Build and improve scripts, integrations, and automations that make data ingestion faster and more reliable. 3. Investigate and resolve technical issues across APIs, data formats, and transfer workflows, with support from core FDEs. 4. Monitor active workflows, identify gaps, and verify that customer data arrives complete and accurate. 5. Work directly with customers and internal teams to communicate progress and move past blockers. 6. Turn recurring issues into better tooling, documentation, and reusable workflows. 7. Take on increasingly complex technical work as your experience and ownership grow. What We’re Looking For 1. Foundational programming skills, including the ability to write and debug basic scripts in Python or a similar language. 2. Familiarity with APIs and comfort using command-line tools and Git. 3. A methodical approach to troubleshooting and willingness to ask for help when needed. 4. Strong ownership, reliability, and attention to detail. 5. Clear written communication with customers and internal teams. 6. Ability to follow runbooks, recognize their limitations, and suggest improvements. 7. Sound judgment around sensitive data and production systems. 8. Curiosity, initiative, and a desire to take on increasing engineering responsibility. Nice to Have 1. Experience with SQL, data pipelines, or large datasets. 2. Familiarity with cloud storage and data-transfer workflows. 3. Experience working in Linux environments. 4. Familiarity with formats such as JSON, CSV, or Parquet. 5. Experience using AI coding tools to build and debug, with careful review of their output. 6. Experience in a startup or customer-facing technical role.

SME

C++ Team Lead

SMESoftware, AI and Data / Business and Consulting

Up to $75/hr

United States

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About this role

In this hourly, remote contractor role, you will work as a C++ Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across C++ AI training projects. You will review AI-generated C++ code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards. You will assess work for code correctness, compile-time validity, runtime behavior, memory safety, performance, algorithmic reasoning, debugging accuracy, readability, maintainability, formatting, instruction-following, and adherence to project-specific rubrics. This role requires strong C++ expertise, English communication skills, excellent attention to detail, 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 C++ quality leadership will help ensure C++ training data is accurate, compilable, efficient, safe, clearly explained, 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 Computer Science, Software Engineering, Computer Engineering, or equivalent professional software engineering experience. - Strong grasp of English to follow guidelines and provide clear technical feedback. - 3+ years of professional experience in C++ development, systems programming, performance engineering, embedded software, backend engineering, code review, QA, or technical mentoring. - Strong understanding of modern C++ standards, RAII, smart pointers, templates, STL containers/algorithms, object lifetime, move semantics, concurrency, exceptions, memory management, and build systems. - Ability to identify issues such as undefined behavior, memory leaks, dangling references, race conditions, inefficient algorithms, non-compilable code, hallucinated APIs, or incomplete explanations. - Familiarity with CMake, GCC/Clang/MSVC, GDB/LLDB, sanitizers, Valgrind, GoogleTest, Catch2, Boost, GitHub, CI/CD, profiling, and static analysis tools is preferred. - Experience leading or supporting remote teams of trainers, reviewers, engineers, coding mentors, or QAs is strongly preferred. - Comfortable using Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and project management systems. - Highly organized and able to maintain style guides, FAQs, trackers, onboarding materials, honeypots, calibration tasks, and quality documentation. - Experience with AI training, data annotation, LLM evaluation, code QA, or rubric-based code review is a strong plus. Responsibilities - Quality monitoring: Spot-check C++ items, identify issues, provide feedback through DMs, and escalate recurring or critical quality problems. - Code review: Evaluate AI-generated C++ code, debugging responses, algorithmic solutions, tests, explanations, and performance recommendations. - Trainer/QA communication: Update contributors on Discord about guideline changes, workflow updates, and C++-specific review standards. - Question handling: Respond to questions around memory safety, compilation, templates, STL usage, concurrency, complexity, testing, and rubric interpretation. - Activation management: DM inactive contributors, track follow-ups, and flag availability issues. - Documentation: Create and maintain C++ style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials. - Onboarding: Run onboarding/training calls covering project expectations, rubrics, and C++ quality standards. - Risk review: Flag unsafe, non-compilable, misleading, inefficient, or non-production-ready C++ recommendations. - Process improvement: Identify recurring quality gaps and build scalable QA processes. Skills - LLM Evaluation - Code Review - Algorithms - C++ QA - Performance - AI Training - Trainer Feedback - Memory Management - C++ - Debugging Additional skills - C++ - Modern C++ (C++11/14/17/20) - Systems Programming - Performance Optimization - Embedded Software - Backend Development - Multithreading - Concurrency - Memory Management - RAII - STL - Templates - Move Semantics - CMake - GCC - Clang - MSVC - GDB - LLDB - Sanitizers (ASan/UBSan/TSan) - Valgrind - Profiling - Static Analysis - Boost - Unit Testing - GoogleTest - Catch2 - Git - GitHub - CI/CD - Code Review - Technical Leadership

micro1

Solar2D Game Developer

micro1Software, AI and Data4 days ago

$70-$130/hr

Worldwide

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Mercor

Frontend Engineer Talent Network

MercorSoftware, AI and Data

$70-$150/hr

Worldwide

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micro1

Software Engineer (Open 3D Engine)

micro1Software, AI and Data4 days ago

$70-$130/hr

Worldwide

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SME

C# Team Lead

SMESoftware, AI and Data

Up to $75/hr

United States

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About this role

In this hourly, remote contractor role, you will work as a C Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across C AI training projects. You will review AI-generated C code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards. You will assess work for code correctness, runtime behavior, .NET ecosystem awareness, type safety, async behavior, debugging accuracy, readability, maintainability, performance, security, test coverage, formatting, instruction-following, and rubric adherence. 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 C quality leadership will help ensure C training data is accurate, executable, idiomatic, secure, clearly explained, 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 Computer Science, Software Engineering, IT, or equivalent professional software engineering experience. - Strong grasp of English to follow guidelines and provide clear technical feedback. - 3+ years of professional experience in C/.NET development, backend engineering, enterprise software, cloud development, code review, QA, or technical mentoring. - Strong understanding of C syntax, OOP, LINQ, generics, collections, exceptions, async/await, tasks, dependency injection, nullable reference types, records, delegates/events, and .NET runtime behavior. - Ability to identify issues such as incorrect logic, non-executable code, flawed async usage, poor error handling, weak type safety, security risks, hallucinated APIs, or incomplete explanations. - Familiarity with .NET, ASP.NET Core, Entity Framework Core, xUnit/NUnit/MSTest, Visual Studio/Rider, NuGet, Azure/AWS, Docker, GitHub, CI/CD, and logging/observability tools is preferred. - Experience leading or supporting remote teams of trainers, reviewers, engineers, coding mentors, or QAs is strongly preferred. - Comfortable using Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and PM systems. - Highly organized and able to maintain style guides, trackers, FAQs, onboarding materials, honeypots, calibration tasks, and quality documentation. - Experience with AI training, LLM evaluation, code QA, or rubric-based code review is a strong plus. Responsibilities - Quality monitoring: Spot-check C items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues. - Code review: Evaluate AI-generated C code, .NET snippets, API examples, debugging responses, tests, architecture explanations, and step-by-step reasoning. - Trainer/QA communication: Update contributors on Discord about guideline changes, workflow updates, and C-specific review standards. - Question handling: Respond to questions around .NET behavior, async/await, LINQ, dependency injection, EF Core, testing, security, and rubric interpretation. - Activation management: DM inactive contributors, track follow-ups, and flag availability issues. - Documentation: Create and maintain C style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials. - Onboarding: Run onboarding/training calls for C contributors. - Risk review: Flag insecure, misleading, non-executable, or non-production-ready C/.NET recommendations. - Process improvement: Identify recurring gaps and improve QA workflows. Skills - C QA - ASP.NET Core - .NET - LLM Evaluation - Code Review - Testing - C - AI Training - Trainer Feedback - Debugging Additional skills - C - Microsoft .NET - ASP.NET Core - Entity Framework Core - LINQ - Async/Await - Dependency Injection - Object-Oriented Programming (OOP) - REST APIs - Web API Development - SQL - Azure - AWS - Docker - Git - GitHub - CI/CD - Unit Testing - xUnit - NUnit - MSTest - Test Automation - Code Review - Technical Mentoring - Team Leadership - Agile Methodologies - Microservices - Logging & Monitoring - Visual Studio - JetBrains Rider

Mercor

Business Intelligence Analyst Talent Network

MercorBusiness and Consulting / Software, AI and Data

$70-$120/hr

Worldwide

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micro1

Python Game Developer (Panda3D)

micro1Software, AI and Data4 days ago

$50-$120/hr

Worldwide

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DataAnnotation

Embedded Systems Developer

DataAnnotationSoftware, AI and Data

Up to $40–$125+ / hour

Worldwide

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About this role

Overview DataAnnotation is looking for an experienced Embedded Systems Developer to evaluate how frontier AI models handle real electrical and electronics engineering work. You bring the judgment you have already built over years of designing, debugging, and shipping hardware. We bring engineering problems the models cannot yet solve on their own. This is a new and growing area for our company, focused on teaching AI to reason correctly about circuits, systems, and physical constraints. Your engineering judgment, your standard for what counts as a correct answer, and the written rationale behind them become the signal that shapes the next generation of engineering tools. What you’ll actually do - Design challenging, realistic engineering problems from your own practice: a circuit to specify, a control loop to stabilize, a power stage to size. - Run those problems through frontier AI models and judge the output against your professional standard. - Compare two model versions on identical prompts and call which performed better, and where each fell short. - Critique model-generated derivations, schematics, component selections, and calculations, and write the reasoning behind your call. - Flag concrete failures with evidence: wrong assumptions, sign and unit errors, unphysical results, invalid topologies, fabricated datasheet values, or off-brief interpretation. Problems draw on whatever you know best: - Analog, RF, and mixed-signal circuits. - Electromagnetics and antennas. - Control and systems. - Devices and materials. - Signal processing and photonics. - Power and energy systems. Roles this fits Common backgrounds: Embedded Systems Developer, Firmware Engineer, Embedded Software Engineer. What we look for - Fluency in English (native or bilingual level). - 2+ years of industry experience in circuit or electronics engineering. - Background in electrical engineering, electronics engineering, or a closely related discipline. - Strong command of circuit analysis and design tradeoffs, and the ability to defend component-level and system-level decisions. - The ability to articulate why an answer is wrong, not only that it is. - Working comfort with AI tools, or the ability to pick them up quickly. - A current, in-progress, or completed Bachelor’s is preferred but not required. - Only applicants based in Australia, Canada, Ireland, New Zealand, the United Kingdom, or the United States will be considered for this role. How it works Apply Qualify Work & get paid Compensation Up to $125+/hr depending on task difficulty and specialization. Many contributors add $100k–$200k a year; some make it their full-time income. About DataAnnotation DataAnnotation is where 1M+ experts train the world’s leading AI models. Hundreds of millions paid to contributors to date, and the average contributor stays 5+ years. Flexible, remote, and always project-available.

SME

C Team Lead

SMESoftware, AI and Data

Up to $75/hr

United States

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In this hourly, remote contractor role, you will work as a C Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across C programming AI training projects. You will review AI-generated C code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected quality standards. You will assess work for code correctness, compile-time validity, runtime behavior, memory safety, pointer logic, portability, performance, debugging accuracy, readability, formatting, instruction-following, and rubric adherence. This role requires strong C expertise, English communication skills, attention to detail, 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 C quality leadership will help ensure C training data is accurate, compilable, safe, efficient, clearly explained, 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 Computer Science, Software Engineering, Computer Engineering, Electrical Engineering, or equivalent professional experience. - Strong grasp of English to follow guidelines and provide clear technical feedback. - 3+ years of professional experience in C programming, systems programming, embedded development, firmware, operating systems, performance engineering, code review, QA, or technical mentoring. - Strong understanding of pointers, arrays, memory allocation, structs, function pointers, preprocessor macros, header files, compilation/linking, undefined behavior, file I/O, bitwise operations, and portability. - Ability to identify issues such as buffer overflows, memory leaks, use-after-free, undefined behavior, invalid pointer arithmetic, race conditions, non-compilable code, hallucinated APIs, or incomplete explanations. - Familiarity with GCC/Clang/MSVC, Make/CMake, GDB/LLDB, Valgrind, sanitizers, embedded toolchains, POSIX APIs, unit testing frameworks, GitHub, CI/CD, profiling, and static analysis tools is preferred. - Experience leading or supporting remote teams of trainers, reviewers, engineers, coding mentors, or QAs is strongly preferred. - Comfortable using Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and PM systems. - Highly organized and able to maintain style guides, trackers, FAQs, onboarding materials, honeypots, calibration tasks, and quality documentation. - Experience with AI training, LLM evaluation, code QA, or rubric-based code review is a strong plus. Responsibilities - Quality monitoring: Spot-check C items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues. - Code review: Evaluate AI-generated C code, debugging responses, pointer/memory examples, algorithmic solutions, tests, and technical explanations. - Trainer/QA communication: Update contributors on Discord about guideline changes, workflow updates, and C-specific review standards. - Question handling: Respond to questions around pointers, memory allocation, compilation, UB, portability, embedded constraints, testing, and rubric interpretation. - Activation management: DM inactive contributors, track follow-ups, and flag availability issues. - Documentation: Create and maintain C style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials. - Onboarding: Run onboarding/training calls for C contributors. - Risk review: Flag unsafe, non-compilable, misleading, memory-unsafe, or non-production-ready C recommendations. - Process improvement: Identify recurring quality gaps and improve QA workflows. Skills - LLM Evaluation - Code Review - C - C QA - C Programming - Pointers - AI Training - Trainer Feedback - Memory Management - Debugging Additional skills - C - Systems Programming - Embedded Systems - Firmware Development - Pointers & Memory Management - POSIX - GCC - Clang - MSVC - Make - CMake - GDB - LLDB - Valgrind - AddressSanitizer (ASan) - UndefinedBehaviorSanitizer (UBSan) - Static Analysis - Profiling - Concurrency - Race Condition Debugging - Secure Coding - Code Review - Unit Testing - CI/CD - GitHub - Performance Optimization - Technical Mentoring - Team Leadership - LLM Evaluation - AI Training Data QA

Mercor

LLM Research Scientist (Pre-training & Computer Vision & Adversarial Robustness)

MercorSoftware, AI and Data

$100-$120/hr

Worldwide

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About this role

We're looking for experienced machine learning researchers with hands-on experience training and improving deep learning models end-to-end, across vision and language. You'll work on well-scoped empirical open-ended ML research problems. Responsibilities - Train image classifiers and generative image models from scratch, and fine-tune open-weight language models. - Get the most out of limited data, compute, and model-size budgets. - Make models robust — to adversarial inputs and to adversarial conversations. - Compress models to meet hard size and latency constraints without sacrificing accuracy. - Diagnose and resolve training issues. Requirements We are looking for candidates with strong expertise in one or more of the following areas: Adversarial Robustness Experience with: - Adversarial training of image classifiers (e.g. PGD-based training, TRADES). - Evaluating robust accuracy under standard threat models (e.g. L∞ attacks, AutoAttack) and avoiding gradient-masking pitfalls. - Managing the robustness–accuracy trade-off and robust overfitting. Efficient Computer Vision Experience with: - Training image classifiers end-to-end, especially for fine-grained recognition (many visually similar classes, few examples per class). - Model compression: quantization, pruning, and knowledge distillation from large teachers into small students. - Deploying models under hard size or latency budgets (on-device, edge, or embedded settings). Generative Image Modeling Experience with: - Training image generative models from scratch: diffusion models, GANs, VAEs, or flow-based models. - Iterating against sample-quality metrics such as FID. - Training-efficiency tricks that produce good generators quickly and at small parameter counts. LLM Post-Training & Behavioral Robustness Hands-on experience with one or more of: - Supervised fine-tuning and preference optimisation (DPO, RLHF, RLAIF) of open-weight language models, including building your own datasets via synthetic generation, noisy or weak supervision, and rejection sampling. - Shaping conversational behaviour over multiple turns: resistance to persuasion and sycophancy, calibrated confidence, and knowing when to accept corrections. - Alignment-style fine-tuning that changes a specific behaviour while preserving general capability. Multilingual Pre-training Experience with: - Training multilingual or low-resource-language models from scratch. - Tokenizer design across scripts and typologically diverse languages. - Balancing highly unequal per-language data (sampling temperatures, cross-lingual transfer) in data-constrained regimes. Additional Areas of Interest Experience in any of the following is a plus: - Scaling laws and training-efficiency research. - Curriculum learning and data ordering. - Model evaluation: benchmark construction, contamination control, statistically sound comparisons. - Uncertainty estimation and model calibration. - Data augmentation and synthetic data for robustness. General Qualifications - 3+ years of machine learning research experience (PhD research counts toward this requirement). - Strong experience with PyTorch, JAX, TensorFlow, or similar ML frameworks. - Degree from a top-100 university, experience at a FAANG or comparable AI company, or an equivalent research track record through publications or impactful open-source contributions. Why Join - Work on cutting-edge machine learning research. - Collaborate with leading AI researchers on challenging, high-impact projects. - Flexible, project-based work with competitive compensation.

micro1

OpenSCAD Developer

micro1Software, AI and Data / STEM4 days ago

$65-$123/hr

Worldwide

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