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!