Defining motion for autonomous systems. Backed by a16z.
About the role
Robotics Infrastructure engineers own the systems that get models running on robots and measure how well they work. Sample projects include: deploying and running learned robot policies (VLAs, imitation learning, DAgger) on real hardware, including inference setup, on-robot tuning, and failure diagnosis Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- Bachelor’s degree or equivalent experience in Computer Science, Robotics, or a related field
- 3+ years of industry experience in software engineering, with exposure to robotics or ML deployment
- Strong Python skills and comfort working in Linux environments
- Experience deploying ML models to real systems, not just training them
- Familiarity with containerization (Docker) and building reproducible deployment workflows
- Have deployed imitation learning, reinforcement learning, or VLA policies on physical robots
More about this role
At XDOF, we’re at an inflection point. Frontier labs are racing to build general-purpose robots, and high-quality training data is the bottleneck. We’re building the foundation behind the foundation models – the data collection systems, operational capability, exabyte-scale data warehouse, and software toolchain – to help our partners drive the field forward.
We’re looking for a Robotics Infrastructure Engineer to build the product and infrastructure that lets us and our partners deploy and evaluate learned robotis policies on real hardware. Examples of things you might work on are: deploying VLAs, imitation learning models, and DAgger workflows onto embodied systems, building the evaluation frameworks that measure how they perform, and shipping the product surfaces that make this accessible to partners.
Robotics Infrastructure engineers own the systems that get models running on robots and measure how well they work. Sample projects include:
deploying and running learned robot policies (VLAs, imitation learning, DAgger) on real hardware, including inference setup, on-robot tuning, and failure diagnosis
designing and building evaluation frameworks that benchmark policy performance...
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