Tesla

Makes electric cars, robotaxis and grid batteries

Reinforcement Learning Engineer - Whole Body Controls, Optimus

Robotics & Autonomous SystemsConfirmed live in the last 24 hours

Full-timePalo Alto, CA, USANo salary listedIn-person

About the Job

Requirements

Proficiency in Python, NumPy, and PyTorch.
Strong reinforcement-learning fundamentals, including policy-gradient and actor-critic methods, with hands-on experience training reinforcement-learning agents.
Curiosity about physics and robotics and eagerness to learn control and dynamics on the job; prior robotics experience is not required.
Equivalent experience through projects, research, or coursework is acceptable.

Responsibilities

Develop end-to-end reinforcement-learning policies for whole-body control spanning locomotion and manipulation, including walking, balancing, disturbance recovery, and manipulating objects.
Design reward functions, action and observation spaces, and curricula; tune and scale reinforcement-learning training.
Improve the sample efficiency, exploration, stability, and sim-to-real robustness of learned policies.
Build large-scale, simulation-based training pipelines.
Evaluate policies in simulation and on hardware, and ship them to a fleet of bots.

Desired Qualifications

Experience with large-scale or distributed reinforcement learning and massively parallel simulation, such as mjlab or IsaacLab.
Experience with reward shaping, curriculum learning, or sim-to-real.
Exposure to robotics or control.

Category	Tesla SI
Location	Palo Alto, California
Requisition ID	244485
Type	Full-time

Job Description

Tesla SI is solving robust embodied intelligence through humanoid robots. On the Whole Body Controls team, you will develop the policies that let Optimus walk, balance, recover from disturbances, and manipulate objects in real-world settings — the layer of the motion stack that turns high-level intent into physically robust motion on real hardware. This role is for engineers with a strong reinforcement-learning foundation who may be new to robotics: we will teach you the physics and control, and you will bring the reinforcement learning expertise that lets the robot learn to move. Most importantly, the policies you deploy will be repeatedly shipped to and used by thousands of humanoid robots in real-world applications. We hire at all levels, including recent graduates with a strong reinforcement learning foundation and a demonstrated project or research record.

Job Responsibilities

Develop end-to-end reinforcement-learning policies for whole-body control spanning locomotion and manipulation: walking, balancing, disturbance recovery, and manipulating objects
Design reward functions, action and observation spaces, and curricula; tune and scale reinforcement-learning training
Improve the sample efficiency, exploration, stability, and sim2real robustness of learned policies
Build large-scale, simulation-based training pipelines
Evaluate policies both in simulation and on hardware, and ship them to a fleet of bots

Job Requirements

Proficiency in Python (numpy, pytorch)
Strong reinforcement-learning fundamentals, including policy-gradient and actor-critic methods, with hands-on experience training reinforcement-learning agents
Curiosity about physics and robotics and an eagerness to learn control and dynamics on the job; no prior robotics experience required
Preferred: large-scale or distributed reinforcement learning and massively parallel simulation (e.g. mjlab, IsaacLab); reward shaping, curriculum learning, or sim2real; any robotics or control exposure
Equivalent experience through projects, research, or coursework is acceptable

About the Company

Tesla

Makes electric cars, robotaxis and grid batteries

Tesla makes electric cars and batteries that store power for homes and utilities, and it develops self-driving software and humanoid robots. In 2023, its Model Y became the first electric vehicle to rank as the world's best-selling car. Buyers order the Model 3 sedan, Model Y SUV, or Cybertruck pickup directly from Tesla instead of through dealers, and they charge on its Supercharger fast-charging network. It also sells Megapack and Powerwall batteries, runs a robotaxi service, and charges drivers a monthly fee for self-driving software that still needs their supervision. Tesla was founded in 2003, with Elon Musk as its lead early investor and a recognized co-founder, and it is based in Austin, Texas.

Company size: 10,001+
Company stage: IPO
Headquarters: Austin, TX
Founded: 2003

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