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- Tasks: Design and refine MuJoCo simulation environments for AI training in robotics.
- Company: Join Alignerr, a leader in robotics and AI simulation.
- Benefits: Fully remote, flexible hours, and freelance autonomy.
- Other info: Engage with a global community of top-tier ML and robotics experts.
- Why this job: Shape the future of intelligent agents and make a real-world impact.
- Qualifications: Hands-on MuJoCo experience and strong reinforcement learning knowledge.
The predicted salary is between 50 - 70 £ per hour.
What if your expertise in robotics and machine learning could directly shape how the next generation of intelligent agents learn to move, manipulate, and interact with the physical world? We're looking for Robotics ML Experts based in or around London with hands‑on MuJoCo experience to design, build, and refine simulation environments that train AI systems to perform real-world tasks—from locomotion and dexterous manipulation to complex multi‑agent coordination. This is a fully remote, flexible contract role for experienced practitioners who live and breathe physics simulation, reinforcement learning, and robot control. If you've spent time wrangling MJCF files, tuning reward functions, and debugging contact dynamics, this role was made for you.
What You'll Do
- Design, develop, and iterate on MuJoCo simulation environments for robotics research and AI training
- Implement and tune reinforcement learning algorithms (PPO, SAC, TD3, etc.) to train agents in simulated tasks
- Define reward functions, observation spaces, and action spaces that produce robust, transferable policies
- Debug and optimize physics simulations—contact models, actuator dynamics, and scene configurations
- Evaluate trained policies for stability, generalization, and sim-to-real transfer potential
- Document environment specifications, training procedures, and experimental results clearly and thoroughly
- Collaborate asynchronously with research teams to align simulation work with broader project goals
- Stay current with the latest advances in robot learning, simulation, and embodied AI
Who You Are
- Strong hands‑on experience with MuJoCo (or MuJoCo via dm_control, Gymnasium/Gymnasium‑Robotics, or similar wrappers)
- Solid understanding of reinforcement learning theory and practical training pipelines
- Proficient in Python and comfortable with ML frameworks such as PyTorch or JAX
- Experienced in defining and shaping reward functions for complex robotic tasks
- Familiar with robot kinematics, dynamics, and control fundamentals
- Able to read and write MJCF/XML model files and understand their physics implications
- Self‑directed, detail‑oriented, and comfortable working independently in an async environment
- Strong written communicator who can document technical work clearly
Nice to Have
- Experience with sim‑to‑real transfer techniques (domain randomization, system identification)
- Familiarity with other physics simulators—Isaac Gym, PyBullet, Drake, or Genesis
- Background in multi‑agent environments or hierarchical RL
- Published research or open‑source contributions in robotics, RL, or embodied AI
- Experience with imitation learning, model‑based RL, or world models
- Graduate‑level coursework or degree in robotics, ML, computer science, or a related field
Why Join Us
- Work on cutting‑edge robotics and AI simulation projects alongside leading research labs
- Fully remote and flexible — work when and where it suits you
- Freelance autonomy with the structure of meaningful, milestone‑driven work
- Directly influence how AI agents learn to interact with the physical world
- Engage with a global community of top‑tier ML and robotics practitioners
- Potential for ongoing work and contract extension as new projects launch
Robotics ML Expert — MuJoCo Simulation employer: Alignerr
Contact Detail:
Alignerr Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Robotics ML Expert — MuJoCo Simulation
✨Tip Number 1
Network like a pro! Reach out to fellow robotics and ML enthusiasts on platforms like LinkedIn or relevant forums. Share your passion for MuJoCo and ask about their experiences—who knows, they might just have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your MuJoCo projects, reinforcement learning algorithms, and any cool simulations you've built. This will give potential employers a taste of what you can do and set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on common questions related to robotics and ML. Be ready to discuss your experience with MJCF files, reward functions, and debugging techniques. Confidence is key, so practice explaining your thought process clearly!
✨Tip Number 4
Don't forget to apply through our website! We love seeing candidates who are genuinely interested in joining our team. Plus, it gives you a chance to showcase your enthusiasm for working on cutting-edge robotics and AI simulation projects.
We think you need these skills to ace Robotics ML Expert — MuJoCo Simulation
Some tips for your application 🫡
Show Off Your MuJoCo Skills: Make sure to highlight your hands-on experience with MuJoCo in your application. We want to see how you've designed and refined simulation environments, so share specific examples of your work that demonstrate your expertise.
Get Technical with Reinforcement Learning: Since this role involves implementing and tuning reinforcement learning algorithms, don’t shy away from discussing your knowledge in this area. We love seeing candidates who can articulate their understanding of algorithms like PPO, SAC, and TD3.
Document Like a Pro: As a strong written communicator, it’s crucial to showcase your ability to document technical work clearly. Include any relevant documentation or reports you've created in the past to give us a taste of your communication skills.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. Don’t miss out!
How to prepare for a job interview at Alignerr
✨Know Your MuJoCo Inside Out
Make sure you’re well-versed in MuJoCo and its intricacies. Brush up on your experience with MJCF files, tuning reward functions, and debugging contact dynamics. Being able to discuss specific projects where you've applied these skills will show your hands-on expertise.
✨Demonstrate Your Reinforcement Learning Knowledge
Be prepared to talk about reinforcement learning algorithms like PPO, SAC, and TD3. Have examples ready that showcase how you've implemented and tuned these algorithms in your past work. This will highlight your practical understanding of the theory and its application.
✨Show Off Your Problem-Solving Skills
Expect questions about debugging and optimising physics simulations. Think of scenarios where you faced challenges and how you resolved them. Sharing specific instances will demonstrate your analytical thinking and ability to troubleshoot effectively.
✨Communicate Clearly and Confidently
Since this role involves documenting environment specifications and collaborating asynchronously, strong written communication is key. Practice explaining complex concepts in simple terms, as this will reflect your ability to convey technical information clearly.