Member of Technical Staff, Research Engineer

Research Engineer

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!