- G2i
- Miami, FL
- Contract
- 3 weeks ago
- $30–$70/hr
Job Description
Before applying
This 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 applicants
This 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 Doing
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Design, build, and iterate on MuJoCo simulation environments for robotics research and AI training
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Implement and tune RL algorithms (PPO, SAC, TD3) to train agents on simulated tasks
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Define reward functions, observation spaces, and action spaces that produce robust, transferable policies
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Debug and optimize physics simulations — contact models, actuator dynamics, scene configs
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Evaluate trained policies for stability, generalization, and sim-to-real transfer potential
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Document environment specs, training procedures, and experimental results clearly
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Collaborate async with research teams and stay current with advances in robot learning and embodied AI
RLHF 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 Need
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Strong hands-on experience with MuJoCo (or via dm_control, Gymnasium-Robotics, or similar)
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Solid understanding of RL theory and practical training pipelines
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Proficient in Python + ML frameworks (PyTorch or JAX)
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Experience defining reward functions for complex robotic tasks
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Familiar with robot kinematics, dynamics, and control fundamentals
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Can read and write MJCF/XML model files and understand their physics implications
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Self-directed, detail-oriented, comfortable working independently in an async environment
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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 Have
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Experience with sim-to-real transfer — domain randomization, system identification
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Familiarity with other physics simulators: Isaac Gym, PyBullet, Drake, or Genesis
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Background in multi-agent environments or hierarchical RL
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Published research or open-source contributions in robotics, RL, or embodied AI
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Experience with imitation learning, model-based RL, or world models
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Graduate-level coursework or a degree in robotics, ML, CS, or a related field
What You Don't Need
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No prior RLHF or AI training experience
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No deep machine learning knowledge — if you can review and critique code clearly, we'll teach you the rest
Logistics
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Location: Fully remote — work from anywhere on the accepted locations list
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Compensation: $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 types
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Hours: Minimum 15 hrs/week, up to 40+ hrs/week available — hours vary by project and are not guaranteed week to week
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Engagement: 1099 independent contractor
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Payment: 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.
