Robotics ML Expert, AI

Before applyingThis role is open to contractors in accepted locations only. Please confirm your country is on the list before applying — we're unable to process applications from unlisted locations. List of accepted countries and locations.For US applicantsThis is a 1099 independent contractor role. It is not compatible with F-1 OPT, STEM OPT, or any visa status that requires W-2 employment, guaranteed hours, or employer sponsorship.We are unable to provide offer letters or employment verification for this role.What You'll Be DoingDesign, build, and iterate on MuJoCo simulation environments for robotics research and AI trainingImplement and tune RL algorithms (PPO, SAC, TD3) to train agents on simulated tasksDefine reward functions, observation spaces, and action spaces that produce robust, transferable policiesDebug and optimize physics simulations — contact models, actuator dynamics, scene configsEvaluate trained policies for stability, generalization, and sim-to-real transfer potentialDocument environment specs, training procedures, and experimental results clearlyCollaborate async with research teams and stay current with advances in robot learning and embodied AIRLHF in one line: Generate code → expert engineers rank, edit, and justify → convert that feedback into reward signals → reinforcement learning tunes the model toward code you'd actually ship.What You'll NeedStrong hands-on experience with MuJoCo (or via dm_control, Gymnasium-Robotics, or similar)Solid understanding of RL theory and practical training pipelinesProficient in Python + ML frameworks (PyTorch or JAX)Experience defining reward functions for complex robotic tasksFamiliar with robot kinematics, dynamics, and control fundamentalsCan read and write MJCF/XML model files and understand their physics implicationsSelf-directed, detail-oriented, comfortable working independently in an async environmentStrong written communicator — a big part of this role is explaining your reasoning clearlyIdentity 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 HaveExperience with sim-to-real transfer — domain randomization, system identificationFamiliarity with other physics simulators: Isaac Gym, PyBullet, Drake, or GenesisBackground in multi-agent environments or hierarchical RLPublished research or open-source contributions in robotics, RL, or embodied AIExperience with imitation learning, model-based RL, or world modelsGraduate-level coursework or a degree in robotics, ML, CS, or a related fieldWhat You Don't NeedNo prior RLHF or AI training experienceNo deep machine learning knowledge — if you can review and critique code clearly, we'll teach you the restLogisticsLocation: Fully remote — work from anywhere on the accepted locations listCompensation: $30–$70/hr based on location and seniority. Note: the majority of projects run at around $30/hr — higher rates apply to senior profiles and specific project typesHours: Minimum 15 hrs/week, up to 40+ hrs/week available — hours vary by project and are not guaranteed week to weekEngagement: 1099 independent contractorPayment: Weekly via PayPal or Stripe⚠️ Important: Hours are project-dependent and can vary week to week. We recommend keeping other work options open alongside this engagement rather than relying on it as your sole source of income.