Robotics Engineer - Navigation focus

general robotics corporation; Redmond (WA); On-site; USD 130,000 - 170,000; Full time

Job summary

General Robotics in Redmond, WA seeks researchers and engineers with a strong background in robotics and machine learning to advance SLAM, navigation, and 3D perception using novel methods and foundation models. You will collaborate across research and engineering, from problem definition to deployment-oriented experimentation.

You will help build efficient robotics pipelines, adapt ML models to robotics tasks, and design high-fidelity simulation environments to improve sim-to-real transfer,

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.

Responsibilities

• Develop new methods and systems that advance the state of the art in robotics, 3D perception, navigation, and foundation models.
• Adapt standard machine learning models and frameworks to robotics applications (e.g. computer vision, SLAM, navigation).
• Build efficient robotics pipelines integrating sensor fusion, perception models, geometric reasoning, and model inference.
• Define research goals informed by practical engineering concerns.
• Design high fidelity simulation environments that advance sim-to-real transfer and enable faster iteration cycles for deploying new robots.
• Contribute to experiments, including designing experimental details, writing reusable code, running model evaluations, and organizing results.
• Partner with customers to deploy robots with navigation capabilities in real production environments.
• Contribute to publications and open-sourcing efforts.

Skills

Robotics

Machine learning

Computer vision

Python

C++

PyTorch

Jax

Education

Bachelor's degree in CS or related field

Master's/PhD in Robotics/CS/Engineering

Tools

AirSim

CARLA

Isaac Sim

Mujoco

Maniskill

Job description

About the Role:

We are looking for strong candidates who have a background in robotics and machine learning, especially with experience in SLAM, robot navigation (classical or learning-based), and geometric foundation models (e.g. VGGT, MapAnything, etc). You will work across research and engineering, from defining research problems and developing new methods to training, simulation, evaluation, and deployment-oriented experimentation.

Responsibilities

• Develop new methods and systems that advance the state of the art in robotics, 3D perception, navigation, and foundation models.

• Adapt standard machine learning models and frameworks to robotics applications (e.g. computer vision, SLAM, navigation).

• Build efficient robotics pipelines integrating sensor fusion, perception models, geometric reasoning, and model inference.

• Define research goals informed by practical engineering concerns.

• Design high fidelity simulation environments that advance sim-to-real transfer and enable faster iteration cycles for deploying new robots.

• Contribute to experiments, including designing experimental details, writing reusable code, running model evaluations, and organizing results.

• Partner with customers to deploy robots with navigation capabilities in real production environments.

• Contribute to publications and open-sourcing efforts.

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 AirSim, CARLA, Isaac Sim, Mujoco, Maniskill among others.

• Experience building efficient robotics pipelines involving sensor fusion and model inference

• Experience working with modern computer vision algorithms and sensors (RGB, RGB-D cameras, LIDAR.), 3D (meshes, point clouds, etc), segmentation, tracking, detection.

• 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]