1234 open jobs
Open roles in AI training, model evaluation, RLHF and data labeling for domain experts. Search, filter, then apply directly on Mercor, micro1, Turing, Ethos, Mindrift, DataAnnotation, Alignerr, Handshake AI, Surge AI, xAI, Vetto or Terac.
This contract role centers on building MuJoCo physics simulations where AI agents practice locomotion, manipulation, and multi-agent tasks. It suits experienced robotics and machine learning practitioners who can design reinforcement learning setups, tune reward functions, and debug contact dynamics. The work is fully remote, asynchronous, and paced by milestones.
This contract role centers on building and refining MuJoCo physics simulations where reinforcement learning agents practice locomotion, manipulation, and coordination tasks. It suits experienced robotics and machine learning practitioners who can design reward functions, debug contact dynamics, and document their work independently in a remote, asynchronous setting.
This contract role centers on building MuJoCo physics simulation environments and training reinforcement learning agents to carry out robotic tasks such as locomotion and manipulation. It suits experienced robotics and machine learning practitioners who are comfortable with physics simulation, policy training and robot control, and who can work independently on milestone-based projects.
This contract role asks a robotics and machine learning specialist to build and refine MuJoCo simulation environments that train AI agents on physical tasks such as locomotion and manipulation. It suits experienced practitioners in physics simulation, reinforcement learning and robot control who can work independently and document their results clearly.
This remote contract role centers on building physics simulation environments in MuJoCo that teach AI agents to move and manipulate objects. It suits experienced practitioners who combine robot control, reinforcement learning, and physics simulation expertise.
This contract role centers on building and refining MuJoCo physics simulation environments where AI agents learn locomotion, manipulation, and multi-agent coordination. It suits experienced robotics and machine learning practitioners who can combine reinforcement learning, robot control, and simulation debugging. Work is remote, asynchronous, and organized around milestones.
This remote contract role centers on building and refining MuJoCo physics simulation environments where AI agents learn locomotion, manipulation, and coordination tasks. It is aimed at experienced robotics and machine learning practitioners who are comfortable with reinforcement learning, robot control, and debugging contact dynamics.
This contract role asks specialists to design, build and refine MuJoCo physics simulation environments that train AI agents on locomotion, manipulation and multi-agent tasks. It suits experienced practitioners in reinforcement learning and robot control who can also document their results clearly. The work is remote with flexible weekly hours.
This contract role asks engineers to write and review step-by-step reasoning traces that show how a language model should plan, use tools, and reach decisions. The output becomes training data meant to make AI systems more reliable on complex, real-world tasks. It suits experienced machine learning engineers and researchers who can work remotely and on their own schedule.
This freelance role asks senior machine learning practitioners to write step-by-step reasoning traces that record how an expert plans, uses tools, and decides through hard technical problems, so that large language models learn to reason the same way. It suits people with deep ML or AI systems backgrounds who can explain their thinking clearly and work independently on open-ended tasks.
This remote contract role involves building coding benchmarks and data pipelines that test how well frontier AI models reason about, debug, and write software. It is aimed at senior software engineers with several years of professional experience who can work across large, multi-language codebases.
This contract role asks a senior software engineer to build and scale the backend infrastructure behind AI products, working closely with machine learning engineers and researchers. It suits experienced engineers who can work independently on production-grade services, data pipelines, and APIs.
This contract role asks machine learning engineers to review and evaluate machine learning code generated by AI models, checking correctness, efficiency, scalability and clarity. Contractors also write their own ML solutions and explain modeling choices so that frontier AI systems improve at this work. It suits experienced ML practitioners who prefer fully remote, asynchronous, self-directed project work.
This remote contract role asks Ruby engineers to review, evaluate and improve backend coding scenarios that are used to train AI systems. It suits experienced developers who can judge code quality, explain their reasoning clearly and work independently on task-based assignments.
This remote contract role asks structural and civil engineers to turn their practical know-how into AI training tasks. Each task is a focused engineering problem with a clear problem statement, a deterministic checker, and a verified reference solution. It suits practicing engineers who use tools such as OpenSees and know design codes, and no AI background is needed.
This is a remote hourly contract for senior systems engineers who will build and tune the C++ infrastructure behind AI data pipelines, annotation tools and model evaluation. The work centers on performance, reliability and production fixes, carried out alongside research and engineering teams. It suits experienced C++ developers with a systems background who want to work on the infrastructure used to train and ship AI models.
This role involves evaluating how well AI models can perform computational biology tasks. Computational biologists and bioinformaticians will design realistic analysis scenarios from their own work, run them through AI systems, and grade the results against professional standards to help benchmark model capabilities.
A Credit Analyst evaluates AI-generated credit analyses to identify hidden default risks and validate underwriting decisions. You will assess cash-flow coverage, leverage ratios, covenants, and collateral while writing credit decisions that serve as training data for machine learning models.
As a Machine Learning Engineer, you will evaluate and improve how AI models reason about machine learning systems, including training dynamics, evaluation design, and deployment strategies. You will write prompts to test model reasoning, identify subtle errors in AI outputs, and provide correct solutions based on real practitioner experience.
ML expert for the evaluation and training of AI models on machine learning tasks and data pipelines (ETL).
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FAQ
AI training, model evaluation, RLHF, red teaming, data labeling and expert review roles, in fields from software and data science to medicine, law, finance, languages and science.
They are done online. Some are limited to residents of certain countries: when the platform publishes that restriction, the listing shows it.
Usually not. Most roles ask for professional experience in your own field. Each listing states the experience the platform requires.
By the hour or by the task, by the platform that hires you. We show the pay only when the platform publishes it. It is not a guarantee of income or hours.
Apply now opens the official posting on Mercor, micro1, Turing, Ethos, Mindrift, DataAnnotation, Alignerr, Handshake AI, Surge AI, xAI, Vetto or Terac, where you complete the application. You need no account here. See how it works.
