Sensing Systems Engineer

Wayve•Sunnyvale, CA

17h•$276,000 - $310,000•Hybrid

About The Position

Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! The role We are looking for a Sensing Systems Engineer to take ownership of the sensing subsystem across our vehicle platforms. This role sits within the Robotics team and operates at the intersection of AV Engineering, Hardware, Vehicle Software, Validation and Product. You will be responsible for ensuring that our sensor stack and its integration into the vehicle platform meet the performance standards required for reliable model development and deployment. This includes defining clear requirements, building robust validation frameworks, and driving system-level decisions. This is a cross-functional role focused on reducing ambiguity in sensing performance and enabling confident, data-driven decisions about vehicle readiness.

Requirements

5+ years of experience in autonomous systems, robotics, automotive, or a closely related field, with direct involvement in real-world system deployment or vehicle bring-up
Strong systems engineering capability, including translating high-level product or model needs into clear, testable sensing requirements
Hands-on experience with at least one primary sensor modality (camera, LiDAR, radar), including integration into real-world platforms such as vehicles or robotic systems
Working knowledge of multi-sensor systems, including both perception sensors (camera, LiDAR, radar) and localization sensors (IMU, GNSS, wheel odometry)
Experience evaluating sensor performance and understanding limitations in real-world conditions
Experience defining metrics, benchmarks, and acceptance criteria for system performance
Experience working closely with multiple stakeholders such as Hardware, Vehicle Software, ML/Perception/Localization, and Product teams

Nice To Haves

Experience in autonomous driving or ADAS systems
Practical experience with sensor calibration, time synchronization, and data alignment
Experience with vehicle platforms or embedded systems
Background in safety-critical or high-reliability systems
Experience on safety standards applied to AV, in particular SOTIF

Responsibilities

Own sensing system performance
Define what “good” looks like for the sensing stack in the context of model development, on-road performance and other applications using sensor data
Translate high-level product needs into measurable sensing requirements
Develop and maintain clear sensing system requirements (e.g., sensing subsystem performance for both perception and localization sensors, calibration quality etc.)
Align requirements across Robotics, AV Product, Hardware, Vehicle SW and Automotive Product
Support Hardware and Vehicle Software teams to ensure correct sensor integration into the vehicle platform
Identify trade-offs and drive decisions on sensor configuration and system design
Provide consultancy on customers new vehicle programs on sensor requirements
Design and implement frameworks to evaluate sensing system performance
Establish benchmarks and acceptance criteria for new vehicle bring-up
Diagnose and resolve sensor-related issues before they impact on-road behavior
Act as the central point of coordination for sensing across teams
Bring clarity to decision-making during ambiguous or fast-moving bring-up phases
Evaluate how sensing quality affects model performance in real-world scenarios
Partner with ML teams to close the loop between data quality and model outcomes