Robotics ML Expert — AI Simulation & MuJoCo
Alignerr · Bengaluru, Karnataka, India
- Hybrid
- Contract
- $150,000 / year
- Bengaluru, Karnataka, India
Job highlights
- Design and build robotics simulation environments.
- Train AI agents using reinforcement learning.
- Optimize physics simulations and robot control.
- Work remotely on cutting-edge AI projects.
- Collaborate with global ML and robotics experts.
About the role
About The Role
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 in Bangalore's thriving AI ecosystem 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.
Organization: Alignerr
Type: Hourly Contract
Location: Remote
Commitment: 10–40 hours/week
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
Key skills/competency
- Robotics ML Expert
- MuJoCo Simulation
- Reinforcement Learning
- Python
- PyTorch/JAX
- Robot Control
- Physics Simulation
- MJCF/XML
- Sim-to-Real Transfer
- Embodied AI
Skills & topics
- Robotics
- Machine Learning
- AI Simulation
- MuJoCo
- Reinforcement Learning
- Python
- PyTorch
- JAX
- Robot Control
- Embodied AI
- Physics Simulation
- MJCF
- Remote
- Contract
- Expert
How to get hired
- Tailor your resume: Highlight MuJoCo, RL, Python, and robotics experience.
- Showcase your portfolio: Include relevant projects, research, or open-source contributions.
- Emphasize remote work skills: Detail your ability to work independently and communicate asynchronously.
- Prepare for technical questions: Be ready to discuss simulation design, RL algorithms, and physics debugging.
Technical preparation
Master MuJoCo environment creation.,Implement PPO, SAC, or TD3 algorithms.,Practice defining reward and observation spaces.,Familiarize with MJCF file structure and physics.
Behavioral questions
Describe a complex simulation challenge.,How do you document technical work?,How do you collaborate asynchronously?,How do you stay updated on AI research?
Frequently asked questions
- What is the typical hourly rate for a Robotics ML Expert at Alignerr?
- As an hourly contract role, the compensation for a Robotics ML Expert at Alignerr is competitive and depends on your experience and the specific project requirements. While a specific rate isn't published, experienced practitioners with strong MuJoCo and RL skills are highly valued. You can discuss your expected rate during the application process.
- Is this Robotics ML Expert role in Bangalore or remote?
- This Robotics ML Expert position is advertised as being in Bangalore's AI ecosystem, but it is a fully remote role. This means you can work from anywhere, offering flexibility regardless of your location.
- What are the core technical skills required for the Robotics ML Expert role?
- The core technical skills for the Robotics ML Expert role include strong hands-on experience with MuJoCo, a solid understanding of reinforcement learning theory and practical training, proficiency in Python, and familiarity with ML frameworks like PyTorch or JAX. Experience with MJCF/XML files and robot kinematics/dynamics is also crucial.
- How important is MuJoCo experience for this Alignerr position?
- MuJoCo experience is very important for this Robotics ML Expert role at Alignerr. The description specifically mentions hands-on MuJoCo experience and the ability to work with MJCF files as key requirements for designing and building simulation environments.
- What is the expected commitment for this contract role?
- The commitment for this hourly contract role as a Robotics ML Expert is flexible, ranging from 10 to 40 hours per week. This allows you to manage your workload based on project needs and your availability.
- Does Alignerr offer full-time positions for Robotics ML Experts?
- This specific role is listed as an hourly contract position. However, the description mentions the potential for ongoing work and contract extensions, suggesting opportunities for continued engagement based on performance and project needs. Full-time positions may be available at other times.
- What kind of projects can I expect as a Robotics ML Expert at Alignerr?
- As a Robotics ML Expert at Alignerr, you can expect to work on cutting-edge AI simulation projects. This includes designing and developing MuJoCo environments, training AI agents for tasks like locomotion and manipulation, and contributing to research in robot learning and embodied AI.