Open AI training and model evaluation roles that call for Deep Learning expertise, gathered from 7 platforms. Part of Data & Machine Learning.
Pay figures cover the 35 open jobs that publish an hourly rate in USD. They are published rates, not a guarantee of income. Last checked on October 8, 2026.
This role involves evaluating and improving large language models' understanding of physics by designing advanced problems, authoring ground-truth solutions, and auditing AI-generated reasoning across quantum mechanics, electrodynamics, thermodynamics, and other domains. It is suited for PhD-level applied physicists who want to contribute to AI training while working independently on a flexible schedule.
A fully remote contract role where PhD-level biochemists create expert-level problems, author gold-standard solutions, and audit AI-generated biochemical reasoning to train and improve scientific AI models. Ideal for biochemists passionate about scientific rigor who want to shape the accuracy of next-generation AI without requiring prior AI experience.
Chemistry experts with a Master's degree help train AI systems to reason through complex scientific problems by designing chemistry problems, evaluating AI outputs, and providing feedback. This remote position suits chemistry specialists who want to apply their expertise to improve how AI models handle scientific content.
This role involves evaluating and improving AI models that process visual data, including images and video. Computer vision and machine learning experts will assess model outputs, identify failure modes, create training annotations, and provide technical feedback to guide the development of AI systems used at scale.
This role involves designing advanced data science challenges, writing benchmark solutions, and auditing AI-generated code to improve AI reasoning and reliability. It is designed for experienced data scientists who want flexible, intellectually demanding work training and evaluating machine learning systems.
This role involves designing complex data science challenges and authoring ground-truth solutions to train and evaluate advanced AI models. Data scientists will audit AI-generated code, identify logical reasoning failures, and provide structured feedback to improve model performance across machine learning, statistical inference, and data engineering domains.
A physics expert will design and evaluate problems across multiple physics domains to help train and refine AI models. The role involves creating rigorous physics problems, developing detailed solutions, assessing AI responses for accuracy and reasoning quality, and providing feedback to improve AI systems' physics comprehension.
This role involves creating physics problems and evaluating AI-generated solutions to train and improve AI models' reasoning abilities. You will work remotely for an AI training platform, using your deep physics expertise to design rigorous problem sets and provide feedback on AI responses across undergraduate to graduate-level physics domains.
This remote contract role asks you to build and refine MuJoCo simulation environments that teach AI agents locomotion, manipulation, and multi-agent coordination. It is aimed at experienced robotics and machine learning practitioners who are comfortable with physics simulation, reinforcement learning, and robot control.
This contract role centers on building and refining physics simulation environments in MuJoCo so that AI agents can learn locomotion and manipulation tasks. It suits experienced robotics and reinforcement learning practitioners who can work independently and asynchronously with research teams.
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 work on reinforcement learning, robot control, and simulation debugging, mostly on their own in an asynchronous, remote setting.
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.
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FAQ
39 Deep Learning AI training jobs are open on SideHustler today. Listings are rechecked against the official postings: the latest check on this list was on October 8, 2026.
Among the 35 open roles that publish an hourly rate in USD, pay runs from $35 to $250 per hour, with a median of $105. These are the rates the platforms publish, not a guarantee of income or hours.
Alignerr (21), Mercor (11), micro1 (3), DataAnnotation (1), Handshake AI (1), Turing (1) and Vetto (1). You apply on the platform itself, which handles screening, contracts and payment.
The most requested areas of expertise on these listings are Deep Learning, Machine Learning, AI Evaluation, Python, Robotics. Each listing states its own requirements.
Apply now opens the official posting on the platform, where you complete the application. You need no account on SideHustler. To see which roles fit your background first, add your resume and every open job is scored against your profile.
