Member of Technical Staff
XDOF
Member of Technical Staff
XDOF
Data pipelines and annotation for robotics
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 hiring generalist software engineers who can work across our robotics platform. Your work could touch anything from our low-level data collection systems, our simulation code, our evaluation pipelines, or our operations management. There’s a huge range of problems to solve here, and the main constant is that you’ll have a problem to solve.
What You’ll Do
Generalist engineers work on whatever has the highest impact. Examples include:
building backend services and APIs for our robotics platform and customer-facing product
building the orchestration layer for workflows that leverage real robotic hardware
developing and implementing the architecture for a real2sim pipeline
scripting integrations between hardware systems, cloud infrastructure, and software services
You might be a good fit if you have:
strong programming skills in Python or C++
the ability to ramp up quickly in unfamiliar codebases, tools, and problem domains
built and shipped software in fast-moving environments where your role wasn’t clearly defined
worked across multiple domains (backend, frontend, data, infra, scripting) even if you’re not an expert in all of them
experience building systems that interact with physical hardware or manage compute-heavy workloads
experience with AI, robotics, or large-scale data systems
Bonus points if you have:
worked in real-time systems, robotics infrastructure, simulation, rendering, 3D engines, or streaming systems
experience working with different sensor systems (video encoding, camera data, perception systems)
familiarity with distributed systems
XDOF builds data pipelines, data-collection tools, and annotation systems that frontier AI labs and robotics companies use to train robots to operate in the physical world. It tackles the data bottleneck in physical AI by combining teleoperation, simulation, and egocentric data collection, then layering in data cleaning, tooling, and annotation to prepare usable datasets. The company differentiates itself through its end-to-end data infrastructure for physical AI, its mix of teleoperation, simulation, and first-person data methods, and its Berkeley-founded background from 2024. Its goal is to enable robots to learn to operate in the real world by providing the pipelines and labels needed for training.
Explore more opportunities at XDOF