Quick overview
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.
Haystack's AI agent can fill in and submit this application for you. How AI auto apply works
Similar jobs
- CO

E11 Bio - Machine Learning Scientist I/IIRecently posted Auto Apply
Convergentresearch · Alameda · On-site · Posted 13 Nov 2026 🇺🇸
GCPAWSComputer Vision+1Technology$130k - $225k/yr - TT
Member of Technical Staff, Applied MLRecently posted Auto Apply
True Talent Solutions Partners · New York · On-site · Posted 13 Nov 2026 🇺🇸
Continuous ImprovementLLMPython+1$175k - $350k/yr - TT
Member of Technical Staff, Reinforcement LearningRecently posted Auto Apply
True Talent Solutions Partners · Remote · Remote · Posted 12 Nov 2026 🇺🇸
LLMPyTorchPython+1$250k - $400k/yr - TT
Member of Technical Staff, ML SystemsRecently posted Auto Apply
True Talent Solutions Partners · Menlo Park · On-site · Posted 12 Nov 2026 🇺🇸
CUDADeep LearningMachine Learning$180k - $260k/yr - LL
Physics-Informed Machine Learning - Postdoctoral ResearcherRecently posted Auto Apply
LLNL · Livermore, CA · Hybrid · Posted 11 Nov 2026 🇺🇸
Deep LearningPyTorchPython+2Healthcare$123.0k/yr - BH
Applied ML Engineer, Agents & AutomationRecently posted Auto Apply
Bask Health · United States · Remote · Posted 12 Nov 2026 🇺🇸
GitAWSContinuous Improvement+11TechnologySalary not listed - BH
Machine Learning Engineering InternRecently posted Auto Apply
Bask Health · United States · Remote · Posted 12 Nov 2026 🇺🇸
SQLGitAWS+16TechnologySalary not listed - BH
Machine Learning Engineer, PersonalizationRecently posted Auto Apply
Bask Health · United States · Remote · Posted 12 Nov 2026 🇺🇸
Next.jsSQLGit+15TechnologySalary not listed - BH
Applied ML Engineer, Care ExperienceRecently posted Auto Apply
Bask Health · United States · Remote · Posted 12 Nov 2026 🇺🇸
OnboardingDrizzleNext.js+18TechnologySalary not listed - BH
ML Systems EngineerRecently posted Auto Apply
Bask Health · United States · Remote · Posted 12 Nov 2026 🇺🇸
DockerGitAWS+12TechnologySalary not listed - BH
Machine Learning Engineer, Search & DiscoveryRecently posted Auto Apply
Bask Health · United States · Remote · Posted 12 Nov 2026 🇺🇸
GitAWSContinuous Improvement+8TechnologySalary not listed - BH
Machine Learning Engineer, Evaluation & ReliabilityRecently posted Auto Apply
Bask Health · United States · Remote · Posted 12 Nov 2026 🇺🇸
GitAWSCompliance+14TechnologySalary not listed