Senior Automotive Sensor Ecosystem Engineer - Autonomous Vehicles

NVIDIA•Us, CA

About The Position

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU serves as the intelligence behind computers, robots, and autonomous vehicles that perceive the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. We pioneered a supercharged form of computing loved by the most demanding computer users in the world - scientists, designers, artists, and gamers. It’s not just technology though! It is our people, some of the brightest in the world, and our diverse company culture make NVIDIA one of the most fun, innovative and dynamic places to work in the world! At the center of NVIDIA's culture are our core values like innovation, excellence and determination and team, that guide us to be the best we can be. As an NVIDIAN, you’ll be immersed in a diverse, encouraging environment where everyone is motivated to perform at their highest level. Come join the team and see how we can make a lasting impact on the world. Our autonomous driving team is building and validating sensing systems that accurately interpret the environment in all contions. We are looking for a Senior Automotive Sensor Ecosystem Engineer to help define and validate the next generation sensor framework and environment for autonomous vehicles.cosystem. In this role, you will track automotive sensor technology development plans. You will perform deep-dive sensor evaluations and analyze real-world performance data. You will provide clear, actionable insights that develop platform-level decisions. The ideal candidate is highly technical, data-driven, comfortable working across vendors and in-house teams, and thrives in ambiguous, fast-paced environments where product definitions evolve.

Requirements

Master’s degree or PhD in EE, CE, ME, Robotics, Physics, Applied Math, or a related field (or equivalent experience).
12+ years of experience in automotive sensing, perception-adjacent sensor engineering, sensor validation, or ADAS/AV systems engineering.
Demonstrated ability to build and sustain positive relationships with sensor suppliers, including driving technical discussions, customer concern paths, and joint issue resolution.
Proven expertise evaluating and characterizing one or more automotive sensor modalities (Camera/Radar/Lidar), with the ability to reason across the full sensor suite.
Strong data analysis skills (e.g., Python, Statistical inference) with experience turning noisy real-world data into defensible conclusions and recommendations.
Demonstrated experience defining validation plans and KPIs, executing structured evaluations, and driving issues to root cause with suppliers and internal stakeholders.
Solid understanding of sensor interfaces and system integration constraints (bandwidth, latency, time synchronization, compute impacts, calibration considerations, and environmental effects).
Clear communication skills: able to write crisp technical reports, present trade studies, and influence architecture decisions across multidisciplinary teams.

Nice To Haves

Hands-on experience with fleet/field data analysis for AV/ADAS sensor performance (large-scale logging, curation, scenario mining, regression tracking).
Background in sensor calibration topics (intrinsics/extrinsics, timestamp alignment, drift monitoring, online/offline calibration validation).
Familiarity with safety and automotive development expectations (SOTIF/functional safety concepts, traceability, validation coverage thinking).
Demonstrated leadership as an IC: creating alignment across teams, mentoring, setting technical direction, and delivering through influence rather than authority.

Responsibilities

Own and maintain end-to-end sensor technology roadmaps across the ecosystem (Camera, Radar, Lidar), including capability tracking, maturity assessment, and risk/mitigation plans.
Build and sustain strong partnerships with sensor suppliers as the technical point of contact—driving roadmap and evaluation engagements, aligning on requirements/validation plans/timelines, leading KPI-based deep-dive sensor assessments (lab, vehicle, and fleet), and providing structured feedback that influences sensor features, quality, and issue resolution.
Lead deep-dive, KPI-driven evaluations of sensors and subsystems by defining goals/acceptance criteria and test methodologies, executing lab/bench characterization, and driving vehicle- and fleet-level validation to quantify real-world performance.
Develop and run data analysis workflows on large-scale logs to quantify sensor quality and system impact (detection range/accuracy, calibration stability, drift, dropouts, false positives/negatives, latency/jitter, time sync).
Validate sensor performance and reliability in real-world conditions by assessing environmental robustness and performing field-degradation analysis to identify failure modes and report reliability trends.
Provide high-quality data, dashboards, and executive-ready readouts to inform Autonomous Vehicle Sensor Architecture and Ecosystem Enablement decisions.
Ensure sensor choices align with long-term technology and product roadmaps (cost, scalability, supply continuity, safety/reliability targets, manufacturability, and integration constraints).
Partner cross-functionally with perception, calibration, platform architecture, validation, functional safety, and supplier teams to close issues and drive sensor readiness for productization.
Influence next-gen sensor architecture tradeoffs (sensor suite composition, placement/FOV coverage, redundancy concepts, synchronization strategy, interfaces, power/thermal budgets, and validation strategy).