Open AI training and model evaluation roles that call for Simulation Analysis expertise, gathered from 7 platforms. Part of Engineering.
Pay figures cover the 40 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 designing self-contained computational fluid dynamics tasks that train and evaluate AI models on aerodynamics and flow physics reasoning. CFD engineers create problem statements, deterministic scoring systems, and reference solutions without needing machine learning expertise, translating their domain knowledge into precise, automatically gradable engineering challenges.
This role involves designing small, self-contained computational fluid dynamics tasks that train and evaluate AI models on engineering reasoning. CFD engineers create problem statements, scoring mechanisms, and reference solutions to teach AI systems about aerodynamics, boundary conditions, and flow physics, without requiring machine learning expertise.
This remote contract role asks mechanical engineers to build and check hard engineering problems that test how AI models reason about physical systems. The work includes writing reference solutions and reviewing AI-generated engineering outputs for accuracy and physical validity. It suits engineers with a graduate degree and solid technical expertise who can explain their reasoning clearly in writing.
This remote freelance role asks mechanical engineers to help train and evaluate AI models on complex engineering problems. Contributors design multi-domain challenges, write reference solutions, and check AI reasoning for accuracy, safety, and compliance with engineering standards. It suits engineers with a graduate degree who want to apply their expertise to AI development, and no prior AI experience is required.
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 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 freelance role centers on building high-fidelity physics simulations of robots, including accurate robot models, simulation environments, and pipelines that help robots learn to walk, grasp, and navigate. It suits engineers experienced with robotics simulators such as MuJoCo, Isaac Sim, or Gazebo who want to narrow the gap between virtual testing and real-world robot behavior. The work is hourly and remote, with written collaboration conducted in English.
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 role involves creating challenging engineering problems and solutions that test AI model capabilities in mechanical reasoning and design. You'll write problems from your specialty, solve them yourself, verify the answers, and evaluate how well AI systems perform on real engineering tasks like component sizing, failure analysis, and design validation.
This role involves evaluating how AI models tackle real-world electrical and electronics engineering problems by designing challenging circuit and systems problems, running them through frontier AI models, and judging the model outputs against professional engineering standards. The position is suited for experienced electrical engineers who can provide detailed technical critiques and written rationales to help train AI systems to reason correctly about circuits, systems, and physical constraints.
DataAnnotation seeks an experienced embedded systems developer to evaluate how AI models handle real electrical and electronics engineering problems. You will design realistic engineering challenges, run them through frontier AI models, judge the output against professional standards, and provide detailed written critiques that help train the next generation of AI engineering tools.
DataAnnotation seeks an experienced hardware engineer to evaluate how AI models handle real electrical and electronics engineering problems. You will design realistic engineering challenges, run them through frontier AI models, judge the outputs against professional standards, and provide detailed written critiques that help train the next generation of AI engineering tools.
Add your resume once. Every open job is scored against your profile, and we email you only when a strong match appears. Free.
FAQ
45 Simulation Analysis AI training jobs are open on SideHustler today. 5 were posted in the last 7 days. Listings are rechecked against the official postings: the latest check on this list was on October 8, 2026.
Among the 40 open roles that publish an hourly rate in USD, pay runs from $35 to $200 per hour, with a median of $95. These are the rates the platforms publish, not a guarantee of income or hours.
Alignerr (16), DataAnnotation (9), Mercor (7), micro1 (7), Mindrift (4), Terac (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 Simulation Analysis, AI Evaluation, Technical Documentation, Mechanical Engineering, CAD Modeling. 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.
