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micro1

Senior Mobile Developer

micro1Software, AI and Data

$50-$100/hr

Worldwide

About this role

Role Title: Senior Mobile Software Engineer Role Type: Contractor (~15 hrs a week) Location: Remote 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. As an expert, you will create Reinforcement Learning Environments that test an AI model’s ability to solve complex mobile software engineering problems related to fixing code, creating features, refactoring code, and optimizing performance. You will be tasked with creating a reproducible environment and a golden reference solution for each problem. Scope of Work 1. Create realistic, interesting, and extremely challenging mobile coding tasks for frontier AI models using your preferred repositories. 2. Design problems that require strong mobile engineering skills, such as tracking down subtle bugs, building non-trivial features, handling application state and lifecycle, or improving performance. 3. Develop tasks relevant to your expertise: cross-platform applications using TypeScript, JavaScript, or Dart; iOS applications using Swift; or Android applications using Kotlin. 4. For each task, define the problem, build a reproducible environment, and write deterministic verifiers that accept correct solutions across different valid implementations while rejecting incorrect, incomplete, or hard-coded approaches. 5. Provide a reference solution showing how the task can be solved. Preferred Qualifications 1. Significant hands-on expertise in at least one of the following mobile development tracks: 2. Cross-platform: TypeScript or JavaScript with React Native, or Dart with Flutter. 3. iOS: Swift with SwiftUI or UIKit. 4. Android: Kotlin with Jetpack Compose or the Android View system. 5. Deep understanding of mobile application architecture, state management, asynchronous programming, and application lifecycle. 6. Proven ability to debug complex mobile applications, resolve bugs, and deliver effective performance improvements. Compensation Structure Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum weekly submission requirements apply and will be communicated during onboarding. Start Timeline & Availability 1. We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.

SME

Java Team Lead

SMESoftware, AI and Data / Business and Consulting

Up to $70/hr

United States

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In this hourly, remote contractor role, you will work as a Java Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Java AI training projects. You will review AI-generated Java 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, object-oriented design, API usage, debugging accuracy, readability, maintainability, performance, security, test coverage, formatting, instruction-following, and adherence to project-specific rubrics. This role requires strong Java 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 Java quality leadership will help ensure Java 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, Information Technology, or equivalent professional software engineering experience. - Strong grasp of English to follow guidelines, communicate with teams, and provide clear technical feedback. - 3+ years of professional experience in Java development, backend engineering, enterprise software, JVM systems, code review, software QA, or technical mentoring. - Strong understanding of Java fundamentals such as OOP, collections, generics, streams, lambdas, exceptions, concurrency, annotations, JVM behavior, memory management, modules/packages, and modern Java features. - Ability to evaluate Java content against detailed rubrics and identify issues such as non-compilable code, incorrect logic, poor exception handling, unsafe concurrency, weak object modeling, inefficient algorithms, hallucinated APIs, or incomplete explanations. - Familiarity with common Java ecosystems and tools such as Spring Boot, Maven, Gradle, JUnit, Mockito, Hibernate/JPA, REST APIs, JDBC, IntelliJ/Eclipse, Docker, GitHub, CI/CD, logging, and profiling tools is preferred. - Experience leading or supporting remote teams of trainers, annotators, reviewers, engineers, 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, code QA, or rubric-based code review is a strong plus. Responsibilities - Quality monitoring: Spot-check Java items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues. - Code review: Evaluate AI-generated Java code, Spring/backend snippets, debugging responses, algorithmic solutions, tests, architecture explanations, and step-by-step reasoning. - Trainer and QA communication: Update contributors on Discord about guideline changes, workflow updates, and Java-specific review standards. - Question handling: Respond to questions around Java syntax, OOP design, collections, streams, concurrency, exceptions, Spring Boot, testing, security, and rubric interpretation. - Trainer/QA activation management: DM inactive contributors, track follow-ups, and flag availability issues. - Documentation: Create and maintain Java style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials. - Onboarding and training: Run onboarding/training calls for Java contributors. - Risk and security review: Flag insecure, misleading, non-compilable, inefficient, or non-production-ready Java recommendations. - Process improvement: Identify recurring quality gaps and improve QA workflows. Skills - Java QA - LLM Evaluation - Code Review - Testing - Spring Boot - Java - JVM - AI Training - Trainer Feedback - Debugging Additional skills - Java - Spring Boot - REST APIs - Microservices - Maven - Gradle - JUnit - Mockito - Hibernate - JPA - JDBC - SQL - Git - GitHub - CI/CD - Docker - IntelliJ IDEA - Eclipse - Code Review - Software Quality Assurance (QA) - Test Automation - Concurrency (Multithreading) - JVM Performance Tuning - Memory Management - Logging (SLF4J/Logback) - Profiling - Technical Mentoring - Team Leadership - Agile/Scrum - Technical Documentation

Mercor

Nuclear Engineering & Safeguards Experts for Red Team

MercorSoftware, AI and Data

$65-$75/hr

Worldwide

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About this role

About the work Mercor is assembling a panel of nuclear domain experts to red-team frontier AI models. The goal is to test whether a model can correctly judge the misuse potential of a technical request — answering legitimate questions fully while refusing genuinely dangerous ones. You will: - Write challenging single-turn prompts in your domain, labelled across three levels: benign, dual-use, and adversarial. - Evaluate the responses that come back against a defined policy standard, and judge whether each was handled correctly. - Write the reference answer; what a correct response looks like, and the technical reasoning for why. Background we're looking for We're looking for fuel-cycle depth plus some exposure to how material is controlled, accounted for, or diverted. Safeguards and nonproliferation experience is the strongest signal. The red-teaming task is to write prompts that pull a model past the boundary; the plausible research framing, the question that looks academic until you know what it's actually asking for — and then to explain in writing why the response was or wasn't acceptable. Examples of relevant backgrounds (Ideally w/Red-teaming experience): Safeguards Analyst / IAEA or Euratom Inspector — material accountancy, inspection regimes, Additional Protocol. Nuclear Engineer, Fuel Cycle — enrichment, reprocessing and criticality, end to end. Nuclear Security Engineer (national laboratory) — MPC&A, insider threat, physical protection design. Nuclear Forensics Scientist — radioxenon monitoring, attribution, detection and characterisation. Nonproliferation Analyst — export control, NSG trigger lists, acquisition and smuggling pathways. What the work requires This is writing-intensive work. Every judgment you make needs a written rationale that a non-specialist can follow. Prior technical writing, published research, or expert witness experience is a strong signal — please include a sample or link. You will also be reading and writing about misuse scenarios in your field for sustained periods. We brief experts on this in advance, and you can pause or step away at any point without penalty. Before you apply Your work here will not involve, and must not draw on, classified or export-controlled information, or anything covered by an NDA or prepublication review obligation. If you hold such obligations you may still be a good fit — tell us in your application and we will scope the work accordingly.

micro1

Hardware Expert (MSc. or PhD)

micro1STEM / Software, AI and Data

$60-$120/hr

Worldwide

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About this role

Hardware Expert (MSc. or PhD) Pay: $60–$120/hour Location: Global, fully remote Job Type: Contractor (~15 hours per week) Schedule: Flexible—you choose the hours and days you work, including weekends if desired micro1 is engaging experienced Hardware Engineers to contribute to AI training projects built around complex, real-world engineering problems. In this role, you will use your technical expertise to create, solve, and evaluate engineering challenges that require sound judgment, quantitative reasoning, and reproducible answers. We are looking for engineers who have personally owned meaningful technical work—such as taking a hardware system into production, validating a model against test data, developing a rigorous verification approach, or diagnosing a difficult failure. We value engineers who can connect first-principles reasoning with practical constraints and produce work that can be independently verified. Scope of Work 1. Create technically rigorous, self-contained hardware engineering problems based on realistic industry or research scenarios. 2. Develop clear reference solutions using engineering calculations, simulations, scripts, experimental reasoning, or other appropriate methods. 3. Use tools such as Python, MATLAB, Simulink, SPICE, Julia, C/C++, test automation platforms, or equivalent engineering software to validate results when relevant. Preferred Qualifications 1. Bachelor’s, Master’s, or PhD degree in Electrical Engineering, Mechanical Engineering, Mechatronics, Aerospace Engineering, Systems Engineering, Applied Physics, or a closely related field. 2. Significant professional or research experience in hardware engineering, product development, systems integration, testing, validation, reliability, or failure analysis. 3. Demonstrated ownership of a substantial engineering problem—for example, a product or subsystem that reached production, a model validated against physical testing, a test system you developed, or a difficult failure you diagnosed. 4. Experience working with Coding Agents is a must Process 1. Apply to the role and complete the screening questions. 2. Complete an AI interview of approximately 30 minutes. 3. Complete the hiring manager review. Compensation Structure Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow. Minimum submission requirements apply.. Start Timeline & Availability We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

SME

C++ Engineer

SMESoftware, AI and Data

Up to $65/hr

17 countries

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About this role

As a C++ Engineer, you will work remotely on an hourly paid basis to review AI-generated C++ code, systems designs, and technical explanations, as well as generate high-quality reference implementations and step-by-step reasoning for complex engineering problems. You will assess solutions for accuracy, clarity, safety, and adherence to the prompt; identify errors in logic, memory handling, concurrency, or performance; fact-check technical information; write high-quality explanations and model solutions that demonstrate correct methods; 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 C++ and systems 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, Electrical/Computer Engineering, or a closely related technical field. - 4+ years of professional experience developing production software in C++ for systems, performance-critical, or large-scale applications. - Expert-level proficiency in modern C++ (C++11 and later), including templates, move semantics, smart pointers, and the STL. - Strong background in systems programming concepts such as concurrency, operating systems, low-level performance optimization, and memory management. - Hands-on experience with C++ build systems, compilers, linkers, debuggers, and profiling or analysis tools. - 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 C++ code reviews and enforcing coding standards for safety, performance, and maintainability. - Comfort working with version control, CI/CD workflows, and automated testing frameworks in modern C++ projects. - 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 C++ code. 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 - Code Review - Performance Optimization - C++ Programming - Memory Management - Remote Contractor - English - Debugging - Concurrency - Systems Programming - Low-Latency Development Additional skills - C++ - Modern C++ (C++11/14/17/20) - STL - Templates - Move Semantics - Smart Pointers - Systems Programming - Concurrency - Multithreading - Memory Management - Performance Optimization - Linux - Operating Systems - CMake - Bazel - GCC - Clang - LLDB - GDB - Profiling - Valgrind - Sanitizers (ASan/TSan/UBSan) - Code Review - Coding Standards - Git - CI/CD - Unit Testing - Google Test (gTest) - Technical Writing

micro1

Human Data Manager, New Grad

micro1Software, AI and Data / Business and Consulting / Finance

Pay not listed

Worldwide

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About this role

Job Title: Human Data Manager, New Grad Job Type: Full-time Location: Remote 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. No prior experience in AI is required — your domain knowledge is what matters. Key Responsibilities 1. Design, build, and manage robust data workflows for accurate annotation, collection, processing, and analysis. 2. Establish and monitor KPIs to optimize operational performance and drive data-driven decision-making. 3. Analyze datasets to uncover actionable insights and present recommendations that accelerate efficiency. 4. Collaborate cross-functionally to align data strategies with overarching business objectives. 5. Develop and maintain comprehensive reporting frameworks tracking key metrics and workflow improvements. 6. Continuously refine processes to ensure scalability, maintain data integrity, and uphold quality standards. 7. Demonstrate ownership and a proactive, hands-on approach to identifying and solving operational challenges. Required Skills and Qualifications 1. Recent Bachelor’s or Master’s graduate in Computer Science, Data Analytics, Industrial Engineering, Operations Management, Economics, Finance or other related fields. 2. Technical aptitude with demonstrated experience in data analysis, annotation, or workflow optimization. 3. Familiarity with operational processes and a passion for increasing efficiency. 4. Ability to interpret and communicate data-driven insights clearly and persuasively, both in writing and verbally. 5. Strong drive to learn, thrive under pressure, and a willingness to work hard in a fast-paced environment. 6. Excellent collaboration skills and attention to detail in managing data quality and validation. Preferred Qualifications 1. Background in engineering or technical fields with operational focus or human data projects. 2. Experience with data visualization tools (such as Excel, Tableau, Power BI) or programming languages (such as Python, SQL). 3. Internship or project-based experience in data management, AI/ML, or process optimization. Regional Hiring Notes: This role is being hired in parallel across multiple regions due to coverage needs, compliance requirements, and time-zone alignment. Responsibilities and expectations are identical; employment terms vary by region.

Mercor

Machine Learning Expert

MercorSoftware, AI and Data

$70-$120/hr

Worldwide

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About this role

The research teams behind the best-known AI models come to Mercor for machine learning 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 machine learning practitioners 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 machine learning practitioners in the network to projects like: - Writing a modeling problem from a system you actually shipped, with the data, the objective, and the constraint, plus the reference answer a model's attempt gets graded against - Grading model-written training and evaluation code: whether the loss matches the objective, whether the eval set leaks, whether the ablation supports the conclusion drawn from it - Flagging where a model proposes an approach that would train cleanly and still fail in production, given distribution shift, label noise, or a metric that rewards the wrong behaviour Comparable machine learning projects have posted at $70 to $120 an hour, set per project by scope and depth. What we're looking for - Professional experience training, evaluating, or deploying machine learning systems - 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 put models in front of real users and dealt with what came back. 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 machine learning pool. When a project needs machine learning 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.

micro1

Software Engineer (Electron.js)

micro1Software, AI and Data9 days ago

Pay not listed

Worldwide

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About this role

Job Title: Software Engineer (Electron.js) Job Type: Full-time Location: Remote The Role We’re building high-fidelity productivity infrastructure for a globally distributed workforce—software that operates quietly, reliably, and intelligently in the background. As a Software Engineer focused on desktop systems, you’ll help design and scale a cross-platform time intelligence application (MacOS + Windows) used daily by thousands of professionals. What You’ll Work On 1. Architect and evolve a cross-platform desktop agent using Electron.js, optimized for performance and minimal resource footprint. 2. Build real-time timekeeping systems with precise event tracking and background execution. 3. Design and implement system-level signal collection (keyboard, mouse, app usage) with strong privacy and efficiency guarantees. 4. Develop offline-first data pipelines with reliable background sync and conflict resolution. 5. Integrate with distributed backend services and internal APIs to enable analytics and reporting. 6. Continuously improve runtime performance, memory efficiency, and fault tolerance. 7. Collaborate with product, design, and backend teams to ship features that directly impact user productivity. What We're Looking For 1. 3+ years building production-grade desktop applications with Electron.js. 2. Strong proficiency in JavaScript/TypeScript and Node.js. 3. Experience designing cross-platform systems (MacOS + Windows) with consistent behavior. 4. Hands-on work with real-time tracking, event streams, or activity monitoring systems. 5. Familiarity with OS-level APIs for capturing user/system interactions. 6. Deep understanding of performance optimization in desktop environments. 7. Strong debugging skills and ability to reason about edge cases in distributed/offline systems. Preferred 1. Experience building productivity, monitoring, or telemetry-driven applications. 2. Knowledge of native OS integrations (permissions, background processes, system hooks). 3. Understanding of security and privacy considerations in user activity tracking. 4. Familiarity with auto-update systems and release management in Electron.

Mercor

DevOps / Platform Engineer Talent Network

MercorSoftware, AI and Data

$70-$150/hr

Worldwide

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SME

C Engineer

SMESoftware, AI and Data

Up to $65/hr

17 countries

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About this role

As a C Engineer, you will work remotely on an hourly paid basis to review AI-generated C code, low-level systems designs, and technical explanations, as well as generate high-quality reference implementations and step-by-step reasoning for complex engineering problems. You will assess solutions for accuracy, clarity, safety, and adherence to the prompt; identify errors in logic, memory handling, concurrency, or performance; fact-check technical information; write high-quality explanations and model solutions that demonstrate correct methods; 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. Your systems-level C 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, Electrical/Computer Engineering, or a closely related technical field. - 4+ years of professional experience developing production software in C for systems, embedded, or performance-critical applications. - Expert-level proficiency in C, including deep understanding of pointers, memory management, undefined behavior, and low-level debugging. - Strong background in systems programming concepts such as concurrency, operating systems, hardware interaction, and performance optimization. - Hands-on experience with build systems, compilers, linkers, and debugging tools commonly used in C development. - 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 safety and maintainability in C codebases. - Comfort working with version control, CI/CD workflows, and automated testing for C projects. - 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 low-level code. 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 - Code Review - Performance Optimization - C - C Programming - Memory Management - English - Debugging - Concurrency - Embedded development - Systems Programming Additional skills - C Programming - Systems Programming - Embedded Systems - Memory Management - Pointers - Low-level Debugging - GDB - Valgrind - Concurrency - Multithreading - Operating Systems - Performance Optimization - Profiling - Compiler Toolchains - GCC - Clang - Linkers - Make - CMake - Cross-compilation - Static Analysis - Unit Testing - CI/CD - Git - Linux - Code Review - Coding Standards (MISRA C) - Undefined Behavior - Hardware Interface Programming - Technical Writing

micro1

AI Jailbreak & Prompt-Injection Security Expert

micro1Software, AI and Data10 days ago

$50-$90/hr

Worldwide

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Role Title: AI Jailbreak & Prompt-Injection Security Expert Role Type: Contractor Location: Remote micro1 is engaging AI Jailbreak & Prompt-Injection Security Experts to contribute to a cutting-edge customer initiative focused on AI safety and robustness. 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. Design and implement advanced methodologies for evaluating AI system safety, focusing on ethical jailbreaks, LLM red teaming, prompt injection, and tool-use abuse scenarios. 2. Create comprehensive cross-domain elicitation strategies to uncover multi-turn and complex adversarial bypass patterns in AI models. 3. Develop, maintain, and update regression test suites that systematically test for jailbreak susceptibility and prompt-injection vulnerabilities. 4. Construct robust evaluation frameworks that stress-test AI models against real-world adversarial threats, aiming to enhance overall system robustness. 5. Collaborate with technical stakeholders to translate security findings into actionable improvements for model safety and risk mitigation. 6. Document methodologies, findings, and best practices in clear, well-structured written reports and presentations for both technical and non-technical audiences. Preferred Qualifications 1. 2+ years of expertise in adversarial machine learning, LLM red teaming, AI safety evaluation, or a closely related security domain 2. Proven experience researching, testing, or uncovering vulnerabilities related to ethical jailbreaks, prompt injection, tool-use abuse, or adversarial AI attacks. 3. Advanced degree (PhD, MS) in computer science, cybersecurity, machine learning, or a relevant discipline, or equivalent operational/professional background. 4. High credibility and recognition within the AI security or adversarial ML community—such as published research, open-source tools, or conference presentations. 5. Exceptional written and verbal communication skills, with a strong focus on clear documentation and collaborative problem-solving. 6. Prior participation in multi-disciplinary projects or cross-functional AI safety initiatives is a plus. 7. Familiarity with current LLM architectures, prompt engineering techniques, and security assessment tools is highly desirable.

Mercor

Machine Learning Engineer Talent Network

MercorSoftware, AI and Data

$70-$250/hr

Worldwide

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SME

C# Engineer

SMESoftware, AI and Data

Up to $65/hr

16 countries

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About this role

This is an hourly-paid, fully remote contractor role where you will review AI-generated responses and/or generate C/.NET engineering content, evaluating reasoning quality and step-by-step problem-solving. You will assess solutions for accuracy, clarity, and adherence to the prompt; identify errors in methodology or conceptual understanding; fact-check technical claims; and rate/compare multiple responses based on correctness and reasoning quality. You will also produce high-quality explanations and model solutions that demonstrate correct methods and clear communication. This role is with SME Careers, a fast-growing AI Data Services company and subsidiary of SuperAnnotate that provides AI training data for many of the world’s largest AI companies and foundation-model labs—your work directly helps improve the world’s premier AI models. 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 related field (or equivalent professional experience). - 2+ years of professional experience using C. - Strong experience with C and the .NET ecosystem (ASP.NET Core, Web APIs, async/await, LINQ). - Knowledge of relational databases and data access patterns (SQL Server and/or PostgreSQL; EF Core and/or Dapper). - Experience with modern engineering practices and tooling (Git, CI/CD, Docker). - Strong advantage: experience solving Medium–Hard algorithmic problems (e.g., LeetCode/HackerRank-style). - Strong English writing skills; Minimum C1 English proficiency. - Highly detail-oriented, able to spot subtle logical/technical issues and explain corrections clearly. - Preferred: prior experience with AI data training, evaluation, annotation, or technical QA of model outputs. - Able to work as an hourly, remote contractor with reliable internet and consistent availability. 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 - Docker - Web APIs - ASP.NET Core - async/await - .NET - C - LINQ - SQL - EF Core - English Additional skills - C - .NET - .NET Core - ASP.NET Core - REST APIs - Web API Development - Async/Await - LINQ - Entity Framework Core - Dapper - SQL - SQL Server - PostgreSQL - Relational Databases - Data Access Layer - Git - CI/CD - Docker - Unit Testing - xUnit - NUnit - Test Automation - Microservices - SOLID Principles - Design Patterns - Algorithmic Problem Solving - Data Structures - Code Review - Technical Writing - English (C1)

micro1

Rust Architect / Backend Developer

micro1Software, AI and Data14 days ago

Pay not listed

Worldwide

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Rust Architect / Backend Developer Pay: $50–$70/hour Location: Global, fully remote Job Type: Contractor (~15 hours per week) Schedule: Flexible—you can choose the hours and days you work, including weekends if desired (As long as you're active) We are looking for a highly skilled Rust Architect / Backend Developer to contribute to an AI-training project involving production Rust, backend architecture, asynchronous and concurrent systems, service design, infrastructure, and technical debugging. The role requires strong programming ability and the judgment to evaluate whether backend systems are correct, reliable, maintainable, and suitable for production use. Scope of Work 1. Solve and validate Rust backend problems involving service behavior, APIs, persistence, concurrency, performance, and reliability. 2. Translate functional requirements, performance targets, and failure-handling expectations into reproducible implementation and testing workflows. 3. Prepare Rust crate workspaces, configuration files, test fixtures, dependency services, databases, and containerized environments. Preferred Qualifications 1. Strong knowledge of Rust, backend service design, APIs, data systems, concurrency, and production software architecture. 2. Experience formulating and completing technical analyses involving backend correctness, performance, scalability, or reliability. 3. Practical proficiency with Rust in substantial professional, research, or open-source software 4. Clear Rust Architecture ownership Process: 1. Apply to the role, filling out the screening questions 2. Complete AI interview (aprox. 30 minutes), reviewed by recruiters) 3. Hiring Manager review Compensation Structure Compensation is output-based; experts are paid per task that meets the project specifications. The time required to complete work may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Experts must submit a minimum of tasks per week. Start Timeline & Availability We typically fill roles within 48 hours and are looking for experts ready to jump in right away. If selected, we expect you to start your first tasks within 24–48 hours of completing onboarding.

Mercor

Senior Data Scientist and Data Engineering Experts

MercorSoftware, AI and Data / Finance11 days ago

$120-$180/hr

Worldwide

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Role Overview Mercor is working with a leading AI research lab on a project to improve how AI systems do real-world data science and data engineering work. We’re looking for senior data scientists and data engineers who have deep experience at top technology, quantitative or financial firms. You’ll use that expertise to train and evaluate frontier AI models. This role is open to candidates based in the United States, United Kingdom, Canada, Australia or New Zealand. Key Responsibilities - Designing realistic, challenging data science and data engineering tasks, including but not limited to exploratory analyses, statistical modeling, machine learning pipelines, ETL and data pipeline design, SQL and Python workflows, and experimentation or A/B test write-ups - Illustrating "what good looks like" by writing precise, task-specific criteria for data science and data engineering deliverables - Applying consistent, evidence-based judgment so that assessments are reproducible and defensible - Taking structured feedback from senior reviewers and iterating on submitted work Ideal Profile - 4+ years of professional data science, data engineering or machine learning experience in one of these settings: - A leading technology or quantitative firm (such as FAANG+, Magnificent 7+, top-tier quant funds or equivalent) with a Mid-senior level title. Applied Scientist, Research Scientist and Machine Learning Engineer/Scientist roles also qualify. - A top financial institution (a leading bank, hedge fund or trading firm) - A top-tier consulting firm, working as a data scientist - A Fortune 100 company, with a senior or manager-level title - Experience may be split across more than one qualifying employer - Strong command of Python, SQL, statistical modeling, machine learning, experimentation and causal inference - Proven ability to turn messy real-world data into rigorous analyses and reliable pipelines - Excellent written English, including the ability to explain technical findings clearly - Bachelor's degree from an English-speaking country - A detail-oriented, consistent approach to evaluating complex work - Comfortable receiving feedback and calibrating judgment against set standards

SME

R Team Lead

SMESoftware, AI and Data / STEM

Up to $65/hr

United States

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In this hourly, remote contractor role, you will work as an R Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across R programming and data-analysis AI training projects. You will review AI-generated R code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure contributors follow expected standards. You will assess work for code correctness, statistical validity, data reasoning, package usage, reproducibility, debugging accuracy, readability, visualization quality, 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 R quality leadership will help ensure R training data is accurate, reproducible, statistically sound, 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 Statistics, Data Science, Mathematics, Computer Science, Economics, Biology, Social Sciences, or related quantitative field. - Strong grasp of English to follow guidelines and provide clear feedback. - 3+ years of experience using R for data analysis, statistics, research, analytics, teaching, coding, or technical review. - Strong understanding of R syntax, data frames, vectors, functions, lists, factors, missing data, tidyverse, base R, statistical modeling, and visualization. - Ability to identify issues such as incorrect statistical assumptions, invalid package usage, non-reproducible code, data leakage, flawed transformations, hallucinated functions, or misleading charts. - Familiarity with dplyr, tidyr, ggplot2, readr, stringr, purrr, data.table, Shiny, R Markdown/Quarto, caret/tidymodels, lme4, survival, Git, and reproducible workflows is preferred. - Experience leading remote teams of trainers, analysts, reviewers, educators, or QAs is strongly preferred. - Comfortable with Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and PM systems. - Highly organized and able to maintain style guides, trackers, FAQs, honeypots, calibration tasks, and onboarding materials. - Experience with AI training, data annotation, LLM evaluation, code QA, or rubric-based review is a strong plus. Responsibilities - Spot-check R programming and data-analysis items. - Review AI-generated R code, statistical explanations, visualizations, data-wrangling steps, and modeling workflows. - Communicate project updates and R-specific standards on Discord. - Answer trainer/QA questions around R syntax, packages, statistical reasoning, reproducibility, plots, and rubric interpretation. - DM inactive contributors and manage activation tracking. - Create and maintain R documentation, style guides, examples, trackers, FAQs, honeypots, and onboarding materials. - Run onboarding/training calls for R contributors. - Flag misleading statistical claims, invalid methods, non-reproducible workflows, or hallucinated packages/functions. - Improve QA processes based on recurring gaps. Skills - Statistics - LLM Evaluation - Code Review - R QA - Data Analysis - Visualization - R - AI Training - Trainer Feedback - tidyverse Additional skills - R - Tidyverse - Base R - Data Analysis - Statistical Modeling - Data Visualization - dplyr - tidyr - ggplot2 - readr - stringr - purrr - data.table - Shiny - R Markdown - Quarto - tidymodels - caret - lme4 - survival - Reproducible Research - Git - GitHub - Code Review - Technical Writing - Quality Assurance (QA) - Team Leadership - Remote Team Management - LLM Evaluation - Data Annotation

micro1

Machine Learning Researcher (MSc. or PhD)

micro1Software, AI and Data / STEM

$60-$120/hr

Worldwide

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Machine Learning Researcher (MSc. or PhD) Pay: $60–$120/hour Location: Global, fully remote Job Type: Contractor (~15 hours per week) Schedule: Flexible—you choose the hours and days you work, including weekends if desired We are looking for highly skilled Machine Learning Experts to contribute to an AI training project involving model development, training and inference systems, numerical computing, performance optimization, and Python. The work involves creating, solving, reviewing, and validating challenging machine-learning engineering tasks. A representative task may require implementing or modifying a model, constructing a reproducible training or inference workflow, optimizing memory or throughput, debugging numerical or system-level failures, and verifying that the resulting implementation satisfies objective correctness and performance requirements. This is a very coding heavy role. Candidates but have experience using coding agents with python in their workflow. What You’ll Work On 1. Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure. 2. Implement model components, data pipelines, evaluation systems, and numerical methods. 3. Build reproducible programmatic workflows using Python and command-line tools. Required Qualifications 1. A master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. 2. Strong professional or research experience in machine learning. 3. Practical proficiency with Python and coding agents. Equivalent tools may also be considered when the candidate demonstrates directly relevant depth. Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment is strongly preferred. Exceptional open-source or academic experience may also qualify. Process 1. Apply to the role and complete the screening questions. 2. Complete an AI interview of approximately 30 minutes. 3. Complete the hiring manager review. Compensation Structure Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Start Timeline & Availability 1. We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

SME

Bash Team Lead

SMESoftware, AI and Data

Up to $65/hr

United States

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In this hourly, remote contractor role, you will work as a Bash Quality Assurance Lead (QAL) to oversee quality, consistency, and trainer performance across Bash/shell scripting AI training projects. You will review AI-generated Bash code and trainer/QA work, evaluate output quality against project guidelines, provide precise written feedback, and ensure that contributors follow expected quality standards. You will assess work for script correctness, command safety, portability, debugging accuracy, error handling, security awareness, readability, maintainability, 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 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 Bash quality leadership will directly help improve the world’s premier AI models by ensuring that shell-scripting training data is accurate, executable, 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, IT, Systems Administration, or equivalent professional experience. - Strong grasp of English to follow guidelines and provide clear technical feedback. - 3+ years of experience with Bash/shell scripting, Linux/Unix systems, automation, DevOps, systems administration, CI/CD, or technical support workflows. - Strong understanding of Bash fundamentals: variables, quoting, conditionals, loops, functions, pipes, redirection, exit codes, signals, process management, file permissions, and POSIX portability. - Ability to identify issues such as unsafe commands, poor quoting, non-portable syntax, missing error handling, incorrect assumptions, hallucinated flags, and destructive operations. - Familiarity with tools such as grep, awk, sed, find, xargs, curl, jq, cron, SSH, Git, Docker, CI/CD pipelines, and Linux package managers is preferred. - Experience leading or supporting remote teams of trainers, reviewers, engineers, or QAs is strongly preferred. - Comfortable with Discord, Google Sheets, Google Docs, trackers, dashboards, GitHub, and PM systems. - Highly detail-oriented and organized; able to maintain style guides, FAQs, trackers, honeypots, calibration tasks, and onboarding materials. - Experience with AI training, data annotation, LLM evaluation, code QA, or rubric-based review is a strong plus. Responsibilities - Quality monitoring: Spot-check Bash items, identify quality issues, provide feedback through DMs, and escalate recurring or critical issues. - Code review: Evaluate AI-generated shell scripts, CLI workflows, automation snippets, debugging responses, and explanations for correctness and safety. - Trainer/QA communication: Update contributors on Discord about new guidelines, workflow changes, and Bash-specific review expectations. - Question handling: Respond to questions around quoting, portability, Linux commands, destructive operations, permissions, pipelines, and rubric interpretation. - Activation management: DM inactive contributors, encourage activation, track follow-ups, and flag availability issues. - Documentation: Create and maintain Bash style guides, trackers, FAQs, examples, honeypots, calibration tasks, and onboarding materials. - Onboarding: Run onboarding/training calls explaining workflows, rubrics, safety expectations, and Bash-specific review rules. - Safety review: Flag unsafe scripts, destructive commands, credential exposure, injection risks, or misleading production guidance. - Process improvement: Identify recurring gaps and build scalable QA processes. Skills - LLM Evaluation - Code Review - Linux - Shell Scripting - AI Training - CLI Tools - Bash - Trainer Feedback - Debugging - Automation Additional skills - Bash Scripting - Shell Scripting - Linux - Unix - POSIX Compliance - DevOps - Systems Administration - Automation - CI/CD - Git - GitHub - Docker - SSH - cron - grep - awk - sed - find - xargs - curl - jq - Linux Package Management - Process Management - File Permissions - Error Handling - Code Review - QA - Technical Writing - Remote Team Leadership - LLM Evaluation - Data Annotation - Google Sheets

Mercor

Legacy Codebase Migration Expert

MercorFinance / Software, AI and Data

$200/hr

Worldwide

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Mercor is partnering with a frontier AI research lab to engage experienced software engineers with deep expertise in legacy codebase migration and modernisation. We are looking for engineers who have personally executed complex migrations across large, production-grade systems, particularly in financial services, fintech/payments, insurance, healthcare, telecom, large technology companies, and other mission-critical enterprises. Strong hands-on experience with production migrations is the primary qualification. What You'll Do - Design, implement, review, and evaluate complex codebase migration and modernisation tasks. - Analyse legacy code, dependencies, APIs, databases, build systems, and infrastructure to determine safe migration approaches. - Preserve functionality, backwards compatibility, data integrity, security, and performance during migrations. - Develop tests and validation strategies to identify migration regressions and behavioural differences. - Evaluate AI-generated migration solutions for correctness, completeness, maintainability, and production readiness. Relevant Migration Experience Candidates should have deep expertise in one or more of the following: - Language/version: Java 8 → 17/21, legacy .NET → modern .NET, Python 2 → 3, PHP 7 → 8 - Language rewrites: COBOL → Java/Python, JavaScript → TypeScript - Frameworks: Angular, Rails, Django, Spring/Spring Boot, ASP.NET, Next.js/Astro, and other major framework upgrades/replacements - Databases & ORMs: Oracle/MySQL → PostgreSQL, SQL → NoSQL, Hibernate → jOOQ, Sequelize → Prisma, raw SQL → ORM - Infrastructure: VMs/bare metal → containers, Docker/Kubernetes, cloud-native architectures - CI/CD: Jenkins/Travis → GitHub Actions, GitLab CI, or modern deployment pipelines - Build/package tooling: Maven → Gradle, Webpack → Vite, CRA → Next.js, npm → pnpm - APIs: REST → GraphQL, HTTP/REST → gRPC, SOAP/legacy APIs → modern interfaces - Authentication: Legacy auth → OAuth/OIDC, SAML/SSO, modern identity and authorisation systems - Repositories: Polyrepo → monorepo using Bazel, Nx, Turborepo, or similar - Testing: Migration of unit, integration, browser, and E2E testing frameworks - Dependencies/SDKs: Replacement of deprecated or EOL libraries, APIs, runtimes, and vendor SDKs Ideal Background - 5+ years of professional software engineering experience, ideally Senior, Staff, Principal, or equivalent. - Personally owned or made substantial technical contributions to large-scale production migrations. - Experience working with mature systems involving technical debt, complex dependencies, legacy integrations, and significant regression risk. - Strong knowledge of compatibility, testing, observability, staged rollouts, rollback strategies, and behavioural equivalence. - Ability to reason deeply about unfamiliar codebases and diagnose subtle migration failures. - Especially valuable: engineers who have modernised core banking, payments, trading, insurance, healthcare, telecom, or other high-reliability systems. - For COBOL/mainframe modernisation, experience with technologies such as z/OS, CICS, JCL, DB2, VSAM, batch processing, and COBOL-to-Java/Python migrations is particularly valuable. Why Join - Apply your migration expertise to help shape how frontier AI models understand and execute complex software modernisation. - Work on technically challenging problems modelled after real-world, production-scale legacy systems. - Contribute expertise developed from large enterprise migrations without needing an open-source maintainer background. - Opportunity for ongoing work as the research program expands.

micro1

Applied Scientists — Machine Learning (MSc. or PhD)

micro1Software, AI and Data / STEM

$60-$120/hr

Worldwide

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About this role

Applied Scientists — Machine Learning (MSc. or PhD) Pay: $60–$120/hour Location: Global, fully remote Job Type: Contractor (~15 hours per week) Schedule: Flexible—you choose the hours and days you work, including weekends if desired We are looking for highly skilled Machine Learning Experts to contribute to an AI training project involving model development, training and inference systems, numerical computing, performance optimization, and Python. The work involves creating, solving, reviewing, and validating challenging machine-learning engineering tasks. A representative task may require implementing or modifying a model, constructing a reproducible training or inference workflow, optimizing memory or throughput, debugging numerical or system-level failures, and verifying that the resulting implementation satisfies objective correctness and performance requirements. This is a very coding heavy role. Candidates but have experience using coding agents with python in their workflow. What You’ll Work On 1. Develop and validate machine-learning models, training pipelines, inference systems, and supporting infrastructure. 2. Implement model components, data pipelines, evaluation systems, and numerical methods. 3. Build reproducible programmatic workflows using Python and command-line tools. Required Qualifications 1. A master’s degree or PhD in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, Statistics, Engineering, or a closely related quantitative discipline. 2. Strong professional or research experience in machine learning. 3. Practical proficiency with Python and coding agents. Equivalent tools may also be considered when the candidate demonstrates directly relevant depth. Experience at a well-established technology company, AI laboratory, research organization, or other recognized engineering environment is strongly preferred. Exceptional open-source or academic experience may also qualify. Process 1. Apply to the role and complete the screening questions. 2. Complete an AI interview of approximately 30 minutes. 3. Complete the hiring manager review. Compensation Structure Compensation is output-based. Experts are paid per task that meets the project specifications. The time required to complete each task may vary depending on the expert’s experience and workflow. Minimum submission requirements apply. Start Timeline & Availability 1. We typically fill roles within 48 hours and are looking for experts who are ready to begin immediately. If selected, you will be expected to start your first task within 24–48 hours of completing onboarding.

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