Robotics Simulation & RL Engineer

Humanoid; Boston (MA); On-site; USD 200,000 - 300,000; Full time

Benefits offered by this job

Health coverage: medical, dental, and,

23 days PTO (accrued)

401(k) with employer match

Equity included

Free daily catered lunch

Collaboration with top engineers

Influence product direction

Job summary

Humanoid in Massachusetts seeks a Robotics Simulation & RL Engineer to design and validate future robot generations using physics simulation and reinforcement learning. You will own URDF models and the CAD → simulation pipeline, guiding actuator sizing, sensor layout, and control strategies.

You will collaborate with mechanical, control, and perception teams, developing tools to evaluate locomotion and manipulation while pushing the platform toward real-world deployment.

Qualifications

• M.Sc. or Ph.D. in Robotics, Mechanical Engineering, Control, or related field.
• Strong foundation in robot kinematics and dynamics.
• Experience with robot simulation environments (MuJoCo, Isaac Sim, Gazebo, or similar).
• Experience with reinforcement learning in robotics or physics-based simulation.
• Experience with URDF or similar robot description formats.
• Strong programming skills in Python and/or C++.
• Experience training RL locomotion or manipulation policies.

Responsibilities

• Design and evaluate new robot platforms using physics simulation.
• Analyze workspace, manipulability, dynamic balance, and torque limits.
• Use reinforcement learning to stress-test robot designs.
• Own and maintain URDF models of current and future robot platforms.
• Maintain the CAD → URDF → simulation pipeline.
• Develop tools and benchmarks to evaluate locomotion, manipulation, and platform robustness.
• Provide quantitative feedback to hardware teams on actuator sizing, joint placement, mass distribution, and sensor layout.
• Collaborate with mechanical, control, and perception teams to guide platform design decisions.

Skills

Robotics fundamentals

Kinematics & dynamics

Robot simulation tools

Reinforcement learning in robotics

URDF / robot descriptions

Python / C++ programming

RL locomotion/manipulation policies

Education

M.Sc. or Ph.D. in Robotics, Mechanical Engineering, Control, or related field

Tools

MuJoCo

Isaac Sim

Gazebo

Job description

Here at Humanoid, we believe in a future where robots amplify human potential. That’s why we’ve set out on a mission to build the world’s most capable, commercially-scalable, and safe humanoid robots. We’re bringing that mission to life with HMND‑01 - our rapidly developed humanoid platform being deployed in real industrial environments - and we’re growing the team to take it even further.

About The Role

We design robots in simulation before building them in hardware.

As a Robotics Simulation & RL Engineer, you will help design and validate future generations of our robotic platforms - including bipedal and wheeled systems - using physics simulation and reinforcement learning.

You will develop tools to determine whether a robot design can perform real-world tasks before committing to hardware. Your work will directly inform robot architecture, actuator selection, sensor placement, and control strategies.

A key responsibility of this role is owning and validating the canonical robot models (URDF and simulation assets) used across simulation and control stacks.

What You’ll Do

• Design and evaluate new robot platforms using physics simulation

• Analyze robot capabilities including workspace, manipulability, dynamic balance, and torque limits

• Use reinforcement learning to stress-test robot designs and explore capability limits

• Own and maintain URDF models of current and future robot platforms

• Maintain the CAD → URDF → simulation pipeline

• Develop tools and benchmarks to evaluate locomotion, manipulation, and platform robustness

• Provide quantitative feedback to hardware teams on actuator sizing, joint placement, mass distribution, and sensor layout

• Collaborate with mechanical, control, and perception teams to guide platform design decisions

What We're Looking For

• M.Sc. or Ph.D. in Robotics, Mechanical Engineering, Control, or a related field

• Strong foundation in robot kinematics and dynamics

• Experience with robot simulation environments (MuJoCo, Isaac Sim, Gazebo, or similar)

• Experience with reinforcement learning in robotics or physics-based simulation

• Experience working with URDF or similar robot description formats

• Strong programming skills in Python and/or C++

• Experience training RL locomotion or manipulation policies

Nice to have:

• Experience with legged, humanoid, or wheeled robots;

• Experience with whole-body control or torque-controlled robots;

• Experience with simulation-driven hardware design;

• Experience building large-scale RL training pipelines.

What We Offer

• Comprehensive health coverage for US‑based employees, including fully paid medical, dental, and vision insurance, with virtual care and employee assistance resources.

• Meaningful time off to rest and recharge: 23 days of PTO (accrued), separate sick leave, and paid company holidays.

• 401(k) retirement plan with a 4% employer match.

• Equity included–we believe builders should share in what they build.

• Free daily catered lunch, snacks, and drinks in‑office.

• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics.

• Freedom to influence the product and own key initiatives.

For this role in Massachusetts, the target base salary range is $200K-$300K USD per year; your placement in that range depends on how your experience maps to our internal leveling.