Staff Software Engineer, Perception

Job description

Job responsibilities

• Lead end-to-end perception engineering efforts, owning the technical pipeline all the way from low-level sensor Hardware Abstraction Layers (HALs) to high-level multi-modal sensor fusion algorithms.
• Jump fluidly across different layers of the perception stack, seamlessly pivoting from raw data drivers to deep learning tracking models by leveraging extensive, hands-on domain knowledge.
• Bridge the gap between theory and execution by quickly productionizing state-of-the-art computer vision and machine learning research into rugged, real-time code.
• Be accountable for high-performance C++ software pipelines on real-time edge computing platforms, ensuring absolute reliability for months-long, autonomous ocean deployments.
• Work closely with Autonomy, Machine Learning, and Hardware teams to integrate and fuse multi-modal data—combining radar, camera, and AIS—to mitigate vehicle motion and wave clutter.
• Carry out day-to-day work utilizing our custom, next-gen state-of-the-art perception software and modern GPU-accelerated environments in accordance with established safety and performance standards.
• Monitor for system inefficiencies, sensor degradation, or algorithmic bottlenecks, take action to mitigate risks, and escalate when processing or power thresholds are exceeded.
• Design and maintain large-scale regression testing and simulation frameworks, utilizing Python to analyze real-world mission telemetry and evaluate algorithm performance.

Job requirements

• 8+ years of professional experience writing production-grade software (primarily C++) for robotics, autonomous vehicles, or aerospace applications.
• Deep, full-stack perception domain knowledge spanning sensor drivers, calibration, target tracking, computer vision, and multi-sensor fusion.
• Proven track record of evaluating academic papers or cutting-edge research and rapidly converting them into optimized, production-ready code.
• Experience deploying GPU-accelerated algorithms and machine learning models to resource-constrained edge devices (e.g., NVIDIA Jetson/AGX).
• Strong track record of technical leadership and cross-functional collaboration to solve hard autonomy problems from concept to real-world deployment.
• BS or MS in Computer Science, Electrical Engineering, Robotics, or a related field.