3 days ago
San Mateo, CA, USAMid Level
H1B sponsor
Responsibilities
- Deploy and run learned robot policies, including VLAs, imitation learning, and DAgger workflows, on physical hardware.
- Build evaluation and benchmarking frameworks for robotic systems, including metrics, result aggregation, and partner-facing reporting.
- Develop product surfaces for configuring, launching, and monitoring model deployments and evaluation runs.
- Build orchestration systems that schedule deployments and evaluation runs across robot stations.
- Integrate LLMs and foundation models into robot workflows for task specification, error recovery, and high-level planning.
- Containerize and package robot-side software stacks for consistent station and deployment setup.
- Bridge on-robot systems with cloud-side compute, storage, and orchestration.
Requirements
- Bachelor’s degree or equivalent experience in Computer Science, Robotics, or a related field.
- At least 3 years of industry software engineering experience with exposure to robotics or ML deployment.
- Strong Python skills and comfort working in Linux environments.
- Experience deploying ML models to real systems rather than only training them.
- Familiarity with Docker and reproducible deployment workflows.
- Experience deploying imitation learning, reinforcement learning, or VLA policies on physical robots is beneficial.
- Experience building robotic-system or ML-model evaluation infrastructure is beneficial.
- Experience with DAgger or other interactive data collection and policy refinement loops is beneficial.
- Experience with ROS or ROS2 and robotics middleware integration is beneficial.
- Experience building product features or partner-facing tools on technical infrastructure is beneficial.
- Comfort working in 0-to-1 environments and strong passion for robotics are beneficial.
Categories
ML EngineeringRobotics
About XDOF
XDOF builds data, software, and operational infrastructure for robotics companies and research labs developing general‑purpose robots and physical AI. It provides scalable data collection, tooling, hardware integration, and services that help teams train, deploy, and manage autonomy systems. The company is privately held and positions itself as an infrastructure partner to frontier labs and robotics builders, with a team drawing experience from Tesla, Google, Applied Intuition, BAIR, Covariant, and Gatik.