Robotics Engineer - Manipulation focus

The role

You will bring state-of-the-art manipulation methods into the GRID platform. You will build production-grade policies that generalize across embodiments including fixed-base robotic arms, mobile manipulators, and humanoids.

What you will do

• Design methods, tools, and infrastructure to push forward the state of the art in robotics and foundation models.
• Define research goals informed by practical engineering concerns.
• Train, adapt, and deploy manipulation foundation models.
• Build synthetic data generation pipelines on high-fidelity simulation platforms and drive sim-to-real transfer.
• Develop data collection, training, and evaluation pipelines as production-quality code.
• Run experiments end to end including experimental design, implementation, evaluation, and reporting.
• Contribute to publications and open-source releases.
• Partner with customers to take manipulation capabilities from prototype to deployed product.

Required 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.

Nice to have

• MS or PhD in Robotics, Computer Science, Computer Engineering, or a related technical field.
• Direct research experience in robot learning, computer vision, or machine learning.
• First-author publications at peer-reviewed AI and robotics venues (NeurIPS, ICML, ICLR, CVPR, ICRA, IROS, CoRL).
• Hands-on experience with modern manipulation policies — VLAs, world action models, reinforcement learning, imitation learning, diffusion or flow-matching policies, or agentic robot policies.
• Experience with high-fidelity simulators such as NVIDIA Isaac Sim, MuJoCo, ManiSkill, AirSim, or CARLA, including domain randomization and sim-to-real workflows.
• Familiarity with modern perception stacks and sensing modalities: RGB and RGB-D cameras, LiDAR, 3D representations (point clouds, meshes), and segmentation, detection, and tracking.
• Judgment about systems constraints — latency, throughput, compute budget, memory — and the ability to factor them into model and architecture choices.

Before you apply

• Role is open to candidates currently based in and authorized to work in the US.
• Must obtain work authorization in the country of employment at the time of hire, and maintain ongoing work authorization during employment.

About the company

General Robotics is building the intelligence grid for physical AI. Headquartered in Redmond, Washington, the company is venture backed and part of Microsoft's Startups Pegasus Program.