Senior Hardware Engineer, Radar

Job description

Job responsibilities

• Lead technical development of radar or lidar sensing systems from early concept, benchmarking, and sourcing through production launch
• Define sensor performance targets, requirements, evaluation criteria, and validation plans based on vehicle, perception, and ODD needs
• Drive sensor benchmarking and technical down-selection across candidate suppliers and technologies
• Lead supplier technical engagement, including requirements reviews, data reviews, architecture discussions, issue resolution, and design maturity assessments
• Guide architecture and tradeoff decisions related to sensing performance, environmental robustness, packaging, thermal constraints, power, diagnostics, manufacturability, and cost
• Work cross-functionally with systems, perception, firmware, validation, vehicle integration, manufacturing, and quality teams to ensure the sensor meets downstream functional and program needs
• Review test data from supplier, bench, track, and vehicle testing; identify performance gaps; determine root cause; and drive corrective actions
• Assess whether supplier evidence is technically credible by reviewing test conditions, assumptions, filtering, sample quality, boundary cases, repeatability, and alignment to sensor physics and system requirements

Job requirements

• Bachelor's degree in Computer Engineering, Computer Science, Electrical Engineering, Robotics or a related field and 7+ years of relevant experience (or Master's degree and 5+ years of relevant experience, or PhD and…
• 8+ years of experience in automotive sensing, with deep hands-on expertise in either radar or lidar and demonstrated technical leadership on complex hardware programs
• Strong first-principles understanding of the relevant sensing modality: Radar: RF fundamentals, range/Doppler/angle estimation, resolution, interference, multipath, ghosting, calibration, synchronization, and…
• Lidar: time-of-flight or FMCW fundamentals, ranging accuracy, reflectivity effects, point cloud quality, contamination, weather impacts, optical alignment, calibration, and environmental robustness
• Strong scripting and analysis capability in python, including hands-on use of NumPy, pandas, Jupyter, and similar tools to parse logs, evaluate sensor performance, trend issues, and build repeatable analysis workflows
• Ability to work directly with sensor data and debug artifacts, including supplier logs, raw captures, decoded outputs, and vehicle test datasets, and determine whether the data is complete, valid, and physically credible
• Practical experience with day-to-day engineering tools such as Wireshark/PCAP analysis, CAN tools (CANoe/CANalyzer or similar), ROS/rosbag or equivalent logging frameworks, point cloud or radar visualization tools, and…
• Ability to independently judge whether supplier test results are correct by evaluating test setup, calibration state, ground truth method, statistical significance, repeatability, boundary conditions, applied filters,…