Robotics Engineer - Manipulation focus

About this Role

We're hiring Robotics Engineers to bring state-of-the-art manipulation methods into the GRID platform. You'll work at the frontier of autonomous manipulation, building production-grade policies that generalize across embodiments — from fixed-base robotic arms and mobile manipulators to humanoids. This is a role for engineers who want their research to ship. You'll move between training runs, simulation, and real hardware in customer environments.

Responsibilities

• 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 — vision-language-action (VLA) policies, world action models (WAMs), reinforcement learning, and agentic robot policies.
• 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: extensible, well-documented, and usable by engineers outside your team.
• Run experiments end to end — experimental design, reusable implementations, model evaluation, and clear reporting of results.
• Contribute to publications and open-source releases.
• Partner with customers to take manipulation capabilities from prototype to deployed product.

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

• 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.

Work Authorization

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