Manipulation Capabilities Engineer

Description

• Collaboration with top‑tier engineers, researchers, and product experts in AI and robotics
• Come up with data preprocessing strategies to improve the quality of collected data.
• Work with the simulation team to set up RL training using digital twin, and then iterate on reward and simulation quality to ensure successful transfer to the real world.
• Expand observation and action spaces with new components required to support novel capabilities, and work with the Teleoperations team to expose these components to robot operators.
• Partner with the data collection organization to drive data collection activities for a specific capability: specify what good data looks like, ensure diversity and coverage, and iterate on instructions.
• Post-train manipulation policies via behaviour cloning and RL; own the full loop from data to deployment.
• Interface with hardware design team to ensure that manipulation team findings regarding the current generation of hardware are reflected in future designs.
• Partner with Teleoperations and Controls teams to improve motion smoothness and teleoperation experience.

Requirements

• Familiarity with deep learning infrastructure: streaming datasets, checkpointing & state management, distributed training, PyTorch or JAX. Ability to profile & debug numerics and write maintainable research code.
• Experience applying RL to robotics problems.
• Freedom to influence the product and own key initiatives
• 3+ years working on robots (industry or research) with shipped artifacts to show for it. A good understanding of modern teleoperation and low-level control stack.
• Experience with neural network post-training.
• Experience training VLA models for manipulation (autoregressive, diffusion or flow-matching based). Familiarity with OpenVLA, Physical Intelligence (π) models, or similar open VLA frameworks.
• Ability to document experiments clearly and communicate trade‑offs crisply.
• Good familiarity with modern software engineering practices.
• Publications at top-tier robotics or deep learning conferences or equivalent open‑source contributions.

Benefits

• Competitive salary plus participation in our Stock Option Plan
• Travel opportunities to our Vancouver and Boston offices
• Office perks: free breakfasts, lunches, snacks, and regular team events
• Paid vacation with adjustments based on your location to comply with local labor laws

Training + Development

Interview process

Visa Sponsorship

Security clearance