Robotics Engineer: Autonomous Manipulation Across Platforms

General Robotics; Redmond (WA); On-site; USD 150,000 - 190,000; Full time

Job summary

General Robotics is hiring Robotics Engineers to advance state-of-the-art manipulation methods for the GRID platform. The role involves building production-grade policies that generalize across robotic embodiments, from fixed-base arms to humanoids, and moving between training, simulation, and real hardware in customer environments.

Ideal candidates have a strong ML/robotics background, experience deploying models at scale, and proficiency in Python and C++.

Qualifications

• Bachelor's degree in CS, CE, or equivalent practical experience.
• Research experience in ML, robotics, and computer vision.
• Experience with robotics algorithms or ML models at scale.
• Python/C++ programming; strong DL framework knowledge (PyTorch/Jax).
• Must obtain work authorization in the US at hire and maintain it during employment.

Responsibilities

• Design methods, tools, and infrastructure to advance robotics and foundation models.
• Define research goals informed by practical engineering concerns.
• Train, adapt, and deploy manipulation policies and related models.
• Build data pipelines and drive sim-to-real transfer.
• Develop production-quality code for data collection, training, and evaluation.
• Run end-to-end experiments and report results clearly.
• Contribute to publications and open-source releases.
• Partner with customers to deploy manipulation capabilities.

Skills

Robotics research

Machine learning

Python

C++

PyTorch

Jax

Computer vision

Education

Bachelor's degree in Computer Science or Engineering

MS or PhD in Robotics/CS/CE

Tools

NVIDIA Isaac Sim

MuJoCo

ManiSkill

AirSim

CARLA

Job description

General Robotics is hiring Robotics Engineers to advance state-of-the-art manipulation methods for the GRID platform. The role involves building production-grade policies that generalize across robotic embodiments, from fixed-base arms to humanoids, and moving between training, simulation, and real hardware in customer environments.

Ideal candidates have a strong ML/robotics background, experience deploying models at scale, and proficiency in Python and C++.