Robotics ML Expert, AI

G2i Inc. • Miami, FL

17h • Remote

About The Position

This role is for a Robotics ML Expert specializing in AI, working as a 1099 independent contractor. The expert will be responsible for designing, building, and iterating on MuJoCo simulation environments for robotics research and AI training. Key tasks include implementing and tuning RL algorithms (PPO, SAC, TD3), defining effective reward functions, observation spaces, and action spaces, and debugging/optimizing physics simulations. The role also involves evaluating trained policies for stability and generalization, documenting experimental results, and collaborating asynchronously with research teams while staying current with advances in robot learning and embodied AI. This is a fully remote position with flexible hours, requiring a minimum of 15 hours per week, with up to 40+ hours available, though hours are project-dependent and not guaranteed.

Requirements

• Strong hands-on experience with MuJoCo (or via dm_control, Gymnasium-Robotics, or similar)
• Solid understanding of RL theory and practical training pipelines
• Proficient in Python + ML frameworks (PyTorch or JAX)
• Experience defining reward functions for complex robotic tasks
• Familiar with robot kinematics, dynamics, and control fundamentals
• Can read and write MJCF/XML model files and understand their physics implications
• Self-directed, detail-oriented, comfortable working independently in an async environment
• Strong written communicator — a big part of this role is explaining your reasoning clearly
• Identity verification: Applicants will be required to verify their identity and confirm they have valid documentation to work as an independent contractor in their country of residence.

Nice To Haves

• Experience with sim-to-real transfer — 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 a degree in robotics, ML, CS, or a related field

Responsibilities

• Design, build, and iterate on MuJoCo simulation environments for robotics research and AI training
• Implement and tune RL algorithms (PPO, SAC, TD3) to train agents on simulated tasks
• Define reward functions, observation spaces, and action spaces that produce robust, transferable policies
• Debug and optimize physics simulations — contact models, actuator dynamics, scene configs
• Evaluate trained policies for stability, generalization, and sim-to-real transfer potential
• Document environment specs, training procedures, and experimental results clearly
• Collaborate async with research teams and stay current with advances in robot learning and embodied AI

What This Job Offers

• Career Level: Senior
• Education Level: No Education Listed
• Number of Employees: 11-50 employees