Robot Learning Engineer - Sim-to-Real Manipulation

Onyx Staffing; New York (NY); On-site; USD 120,000 - 170,000; Full time

Job summary

Onyx Staffing is seeking talent to bridge sim-to-real gaps for humanoid robots in New York City. You will develop high-fidelity simulation tasks and evaluation environments, train manipulation policies, and push learned behaviors from simulation to hardware.

The role emphasizes strong fundamentals in simulation and ML, with a focus on practical deployment on real robots and scalable data generation workflows.

Qualifications

• 4+ years in robot simulation or robot learning.
• Experience deploying learned behaviors on real robots.
• Strong fundamentals in simulation, system identification, and sim-to-real.
• Proficiency in Python and a modern ML framework.

Responsibilities

• Build high-quality simulated tasks, assets, and evaluation environments.
• Train and evaluate manipulation policies.
• Develop robust methods for transferring learned behavior from sim to physical robots.
• Create tools that accelerate data generation, training, and evaluation.

Skills

Robot simulation

Robot learning

Python

ML frameworks

Job description

Onyx Staffing is seeking talent to bridge sim-to-real gaps for humanoid robots in New York City. You will develop high-fidelity simulation tasks and evaluation environments, train manipulation policies, and push learned behaviors from simulation to hardware.

The role emphasizes strong fundamentals in simulation and ML, with a focus on practical deployment on real robots and scalable data generation workflows.