Robotics Engineer - Humanoids focus

General Robotics; Redmond (WA); On-site; USD 140,000 - 190,000; Full time

Job summary

General Robotics, based in Redmond, WA, seeks researchers with strong robotics and ML backgrounds to train and deploy RL/IL policies for loco-manipulation on humanoid robots. You will design high‑fidelity simulators to improve sim-to-real transfer, define practical research goals, and contribute to publications while collaborating with the deployment team to ship policies to customer sites.

The role emphasizes hands-on research and real-world deployment, with opportunities to influence

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, a relevant technical field, or equivalent practical experience.
• Research experience in machine learning, robotics, and computer vision.
• Experience with developing robotics algorithms or machine learning models at scale.
• Programming experience in Python/C++. Good understanding of deep learning frameworks like PyTorch or Jax.
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Responsibilities

• Train and deploy RL/IL policies for loco-manipulation tasks that perform reliably in the real world, measured by field task success rate.
• Design high fidelity simulation environments that advance sim-to-real transfer and reduce the gap between simulation training performance and real-world deployment, enabling faster iteration cycles.
• Define research goals informed by practical engineering concerns.
• Contribute to experiments, including designing experimental details, writing reusable code, running model evaluations, and organizing results.
• Contribute to publications and open-sourcing efforts.
• Partner with the robot deployment team to ship RL trained policies to production customer sites, owning the entire pipeline from research to deployment

Skills

Python

C++

Machine Learning

Reinforcement Learning

Robotics

Vision

Education

Bachelor's degree in CS/CE or equivalent

Master's/PhD in Robotics/CS/CE

Tools

Isaac Lab

Mjlab

ManiSkill

MolmoSpaces

Job description

About the Role

We are looking for strong candidates who have a background in robotics and machine learning, especially with experience in Reinforcement Learning, Whole-Body Control and Humanoid Locomanipulation. This role offers a unique mix of conducting research and deploying whole body humanoid models.

Responsibilities

• Train and deploy RL/IL policies for loco-manipulation tasks that perform reliably in the real world, measured by field task success rate.
• Design high fidelity simulation environments that advance sim-to-real transfer and reduce the gap between simulation training performance and real-world deployment, enabling faster iteration cycles.
• Define research goals informed by practical engineering concerns.
• Contribute to experiments, including designing experimental details, writing reusable code, running model evaluations, and organizing results.
• Contribute to publications and open-sourcing efforts.
• Partner with the robot deployment team to ship RL trained policies to production customer sites, owning the entire pipeline from research to deployment

Minimum Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Research experience in machine learning, robotics, and computer vision.
• Experience with developing robotics algorithms or machine learning models at scale.
• Programming experience in Python/C++. Good understanding of deep learning frameworks like Pytorch or Jax.
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment

Desired Qualifications

• Master's/PhD in Robotics, Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience.
• Direct experience in robotics, computer vision, or machine learning research.
• First author publications at peer-reviewed AI and robotics conferences (e.g., NeurIPS, CVPR, ICML, ICLR, ICRA, IROS, CORL).
• Experience with high fidelity simulation platforms such as Isaac Lab, Mjlab, ManiSkill, MolmoSpaces etc.
• Experience working with training and deploying policies for whole-body humanoid tasks - reinforcement learning, imitation learning, and classical approaches
• Experience working with modern computer vision algorithms and sensors (RGB, RGB-D cameras, LIDAR.), 3D (meshes, point clouds, etc.), segmentation, tracking, detection.
• Experience with domain randomization, reward shaping, and the engineering needed to bridge sim-to-real gap for humanoid policies
• Experience working with real-world deployment of proprioceptive and visual humanoid policies
• Good understanding of systems considerations and the ability to factor these into model choices.

About General Robotics

General Robotics is building the intelligence grid for physical AI - the platform that makes any robot, from robotic arms to humanoids, genuinely intelligent. Headquartered in Redmond, Washington, we're venture backed, including by Accenture, who invested in General Robotics in 2026 to advance Physical AI-powered robotics in manufacturing and logistics, and we're also part of Microsoft's Startups Pegasus Program. Our team's work spans some of the most widely adopted robotics and AI research to come out of Microsoft Research, Google Research and DeepMind - including AirSim, PACT, ClimaX, Tensorflow Object Detection and VideoPoet.

Work Authorization

This role is open to candidates currently based in and authorized to work in the US.

Equal Opportunity Employer

General Robotics is an equal opportunity employer. We do not discriminate on the basis of any status protected by applicable law.

Accommodations

If you need a reasonable accommodation during the application or interview process, please contact: [e-mail]