Robotics Simulation & Policy Learning Engineer

VeeAR Projects Inc.; New York (NY); On-site; USD 120,000 - 190,000; Full time

Job summary

VeeAR Projects Inc. in New York seeks a robotics AI researcher to own the pipeline from environment to deployed behavior, building high-fidelity simulators and defining manipulation tasks for robotic platforms.

You will scale data generation, train deployable policies, and drive sim-to-real transfer. Collaborate with controls, perception, mechanical, and the learning team to turn target behaviors into safe, repeatable motion on arms and humanoids, using Isaac Sim/MuJoCo/Gazebo/SAPIEN.

Qualifications

• BS, MS, or PhD in Robotics, Computer Science, ML, EE, ME, or related field.
• 4+ years building simulation environments and training/deploying robot policies on real hardware.
• Deep experience with major robotics simulators and building/tuning environments.
• Demonstrated sim-to-real transfer with domain randomization and calibration.
• Strong grasp of RL and/or imitation/diffusion policies; familiarity with VLAs/world models.
• Experience scaling data generation for policy training and pipelines.

Responsibilities

• Build and maintain high-fidelity simulation environments and task definitions for manipulation.
• Train deployable robot policies using RL, imitation/diffusion, VLAs, or world models.
• Close the sim-to-real gap with domain randomization and system identification.
• Scale data generation including synthetic data, teleoperation, and curricula.
• Collaborate with controls, perception, mechanical, and learning teams to realize safe, repeatable motion.

Skills

Robotics simulation

Robot policy training

Domain randomization

Sim-to-real transfer

Python

C++ familiarity

Reinforcement learning

Imitation learning

World models

Education

BS, MS, or PhD in Robotics or related field

Tools

Isaac Sim/Lab

MuJoCo

Drake

Gazebo

SAPIEN

Genesis

Job description

VeeAR Projects Inc. in New York seeks a robotics AI researcher to own the pipeline from environment to deployed behavior, building high-fidelity simulators and defining manipulation tasks for robotic platforms.

You will scale data generation, train deployable policies, and drive sim-to-real transfer. Collaborate with controls, perception, mechanical, and the learning team to turn target behaviors into safe, repeatable motion on arms and humanoids, using Isaac Sim/MuJoCo/Gazebo/SAPIEN.