Research Engineer

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!