About the role
Research Engineer
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.
Our research teams move fast and produce breakthrough work, but research code and production code are different things. We’re looking for a Research Engineer to bridge that gap: someone who can read a research prototype, understand it deeply, and turn it into something that runs reliably at scale on real hardware. You can expect to float across teams to wherever the highest-priority needs are, across perception, ML, and data infrastructure.
What You’ll Do
Research engineers take prototype code and make it production-grade. Sample projects include:
- taking a research perception pipeline (pose estimation, SLAM, calibration) and hardening it for reliable, real-time execution on embedded platforms
- profiling and optimizing performance-critical code at the CPU, memory, and GPU level using tools like perf, NSight, and custom microbenchmarks
- writing and debugging CUDA kernels for low-level acceleration of compute-heavy workloads
- integrating research outputs into the production codebase with proper testing, error handling, and observability
- containerizing and packaging workloads (Docker) so they can be scaled and deployed by the infrastructure team
- understanding and leveraging the infrastructure team’s orchestration and compute systems to hand off production-ready workloads cleanly
- working with researchers to understand algorithmic intent and make informed tradeoffs between accuracy, latency, and resource usage
About You
Baseline skills
- 3+ years of industry experience in software engineering with a focus on systems, performance, or production ML
- strong C++ proficiency, including modern C++ (C++17/20), memory management, and performance-conscious coding patterns
- CUDA programming experience: ability to write, profile, and debug GPU kernels
- experience with CPU performance optimization: profiling, cache behavior, SIMD, latency reduction
- proficiency with Python and familiarity with ML frameworks (PyTorch, TensorFlow) at the level needed to read and modify research code
- comfort with Linux systems, including build systems, debugging tools, and containerization
You might be a good fit if you
- have taken research or prototype code and shipped it in a production system
- have worked on real-time or embedded systems where latency and resource constraints matter
- have experience with perception, computer vision, or robotics systems
- have optimized model inference for deployment (TensorRT, ONNX Runtime, or similar)
- understand the full lifecycle from research notebook to containerized, monitored production service
- are very comfortable working in 0→1 environments
- are mission-driven and passionate about robotics: work at XDOF is fast-paced and constant. We hope you love what you’re going to be doing, because you’ll be doing a lot of it!