Robotics Learning Engineer: Sim-to-Real Expert in NYC

Alexander Chapman; California (MO); On-site; USD 140,000 - 200,000; Full time

Job summary

Alexander Chapman is partnering with a robotics company building and deploying humanoid robots in real factory environments. They seek a Simulation & Robot Learning Engineer to own the pipeline from high-fidelity simulation to policies that transfer onto physical robots.

In NYC on-site, you will lead simulation development, data generation, and policy deployment, with heavy focus on integrating Isaac Sim, MuJoCo, Gazebo, and related tools.

Qualifications

• 4+ years hands-on experience building simulation environments.
• Experience deploying learned policies on real robots.
• Deep experience with Isaac Sim, MuJoCo, Drake, Gazebo, SAPIEN, Genesis.

Responsibilities

• Build and tune simulation environments, assets, physics, scenes, and manipulation tasks.
• Train robot policies using RL, imitation learning, diffusion policies, VLAs, and/or world models.
• Close the sim-to-real gap through domain randomization, system identification, calibration, and real-world debugging.
• Build scalable synthetic data, teleoperation, procedural generation, and automated curriculum pipelines.
• Use agentic AI to automate environment, task, reward, evaluation, and data generation.
• Develop benchmarking infrastructure that makes simulation performance predictive of hardware performance.

Skills

Python

PyTorch

JAX

C++

Robotics

Reinforcement Learning

Imitation Learning

Simulation

Tools

Isaac Sim

MuJoCo

Gazebo

SAPIEN

Drake

Job description

Alexander Chapman is partnering with a robotics company building and deploying humanoid robots in real factory environments. They seek a Simulation & Robot Learning Engineer to own the pipeline from high-fidelity simulation to policies that transfer onto physical robots.

In NYC on-site, you will lead simulation development, data generation, and policy deployment, with heavy focus on integrating Isaac Sim, MuJoCo, Gazebo, and related tools.