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