Member of Technical Staff, Robotics Infrastructure

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 model evaluation platform – 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 robotics policies on real hardware. Examples of things you might work on: deploying VLAs, building our evaluation pipeline, orchestrating our simulation pipeline, and scaling our different products across a huge number of robots and customers.
What You’ll Do
Robotics Infrastructure engineers own the systems that get models running on robots. Sample projects include:

• deploying and running learned robot policies (VLAs, WAMs, DAgger) on real hardware

• scaling our deployments to a huge number of robots

• designing and building evaluation frameworks that benchmark policy performance on physical robots, with metric definition, result aggregation, and partner-facing reporting

• building the product that lets partners configure, launch, and monitor evaluation runs and model deployments

• building orchestration systems that schedule evaluation runs and model deployments across robot stations

• integrating LLMs and foundation models into the evaluation pipeline

• containerizing and packaging robot-side software stacks so new stations and deployments can be brought online quickly

You might be a good fit if you have:

• strong programming skills in Python or C++

• deployed code to real hardware or have deployed policies onto robotic systems

• experience designing systems for the cloud

• prior experience with AI, robotics, or large-scale data systems

• built product features or partner-facing tools on top of technical infrastructure

Bonus points if you have:

• worked in real-time systems, simulation, rendering, 3D engines, or streaming systems

• experience working with different sensor systems (video encoding, camera data, perception systems)