Senior Hardware Engineer, Lidar

Latitude AI (lat.ai) is building the future of Ford’s autonomy roadmap to make travel safer, less stressful, and more enjoyable for everyone. Bringing this vision to scale, our fully in‑house developed hands‑free ADAS platform will debut on Ford’s all‑new Universal Electric Vehicle in 2027.

When you join the Latitude team, you’ll work alongside leading experts across machine learning and robotics, cloud platforms, mapping, sensors and compute systems, test operations, systems and safety engineering – all dedicated to redefining the relationship between people and their vehicles for millions of customers.

The hardware sensing team is responsible for the benchmarking, characterizing, and integration of all sensors. The team works cross‑functionally with systems, perceptions, vehicle integration to ensure the sensors meet Latitude’s ODD requirements and perception requirements, and that they are integrable and reliable in Ford’s series vehicles. Members of the team are expected to understand sensing from a first‑principle approach and ensure those principles are designable and manufacturable.

We keep a breadth of all sensing technology, sensing vendors, and integration technologies. Members are expected to be highly multidisciplinary, as successful sensor integration requires expert understanding across many disciplines – from hardware and software.

• 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 trade‑off 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.
• Lead technical reviews and challenge unsupported claims, weak correlation, incomplete validation, and conclusions that do not match observed data or first‑principles behavior.
• Establish technical plans, milestones, risks, and mitigation strategies to keep sensor programs on track toward nomination and launch.
• Communicate technical status, open issues, and trade‑offs clearly to engineering leadership and cross‑functional partners.

• 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, or PhD and 2+ years).
• 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 environmental effects;
  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 Num Py, pandas, Jupyter, and similar tools to parse logs, evaluate sensor performance, trend issues, and build repeatable analysis workflows.
• Ability to work directly with…