Sensor Technology Engineer

Wayve

. Define sensor-system requirements and quantitative KPIs derived from driving use cases, ODD and product constraints .

Posted 11/9/2026full-timeSunnyvale • California • United StatesMid-LevelSenior💰 $209,700 - $238,250 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates extensive experience in automotive camera, radar, and lidar engineering, with a strong focus on sensor integration, image quality evaluation, and data analysis using Python or MATLAB. Capable of defining technical requirements and collaborating effectively with OEMs, suppliers, and cross-functional teams to ensure successful product development and validation.

Highest-signal resume keywords

Automotive Camera EngineeringSensor IntegrationImage Quality EvaluationData Analysis Using PythonCollaboration With OEMs

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Camera Systems KnowledgeImage SensorsExposureHDRISP PipelinesCalibrationSensor CharacterisationADAS Sensor ValidationRadar FundamentalsLidar Fundamentals

Soft Skills

Clear CommunicationTechnical Decision-MakingCollaboration Across Teams

Tools & Technologies

PythonMATLABMeasurement ToolsData Analysis Tools

Industry Keywords

ADASAV ProgramsMass-Production Sensor IntegrationFleet-Data AnalysisIEEE P2020 ConceptsUltrasonic SensorsSerDesSensor ConfigurationSensor Synchronisation

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

Define sensor-system requirements and quantitative KPIs derived from driving use cases, ODD and product constraints
Develop camera-system concepts covering sensor/module selection, variants, field of view and placement
Evaluate camera image quality, including exposure, HDR, ISP, LED flicker, low-light performance and image artefacts
Define camera mounting and vehicle-integration requirements for OEMs and Tier 1s
Ensure sensor characteristics, installation assumptions and calibration requirements remain consistent across development and production programs
Analyze fleet, simulation, replay and validation data to understand sensor performance and its impact on system KPIs
Define test requirements, review results and support hands-on lab and vehicle testing
Support sensor bring-up and hardware/software integration debugging
Work directly with camera, radar and lidar suppliers on technical requirements, sample evaluation and integration constraints
Support radar integration topics including mounting, radome/fascia effects and interference
Support lidar and other sensing technologies such as ultrasonics where required
Answer technical camera and sensor questions from customers and partners
Maintain sensor requirements, imaging guidelines, test specifications and technical recommendations
Automate sensor-data analysis and reporting using Python
Help identify production and manufacturability constraints early as customer programs move from development toward production

Requirements

What you’ll need

5+ years of hands-on experience in automotive camera, radar or lidar engineering
Delivered technical work on automotive programs from requirements through integration, validation and verified results
Strong knowledge of camera systems, including image sensors, exposure, HDR, ISP pipelines, calibration and image artefacts
Practical experience with camera integration, image quality, sensor characterisation or ADAS sensor validation
Working knowledge of radar and/or lidar fundamentals and vehicle-integration constraints
Experience defining camera mounting and integration requirements with OEMs or Tier 1s, including alignment tolerances, windshield or cover-glass effects, occlusion and mount rigidity
Used measurement and data analysis to make technical decisions, including image-quality evaluation using standard charts, tools and methods
Comfortable working across hardware and software teams and directly with suppliers, OEMs and customers
Able to use Python or MATLAB for engineering analysis, automation and reporting
Able to write clear requirements, test specifications and concise, data-backed recommendations
Experience with production ADAS or AV programs, mass-production sensor integration, ML-based perception, fleet-data analysis, replay-based validation, radome/fascia evaluation, IEEE P2020 concepts, ultrasonic sensors, SerDes, sensor configuration or synchronisation is a strong advantage

Benefits

Comp & perks

Salaries benchmarked against the market annually
Meaningful equity, sharing in the ownership and long term success of Wayve
Relocation support and visa sponsorship where applicable
Hybrid working, core hours and the chance to work hands on in vehicle workshops and labs
Learning and development budgets with support for training, conferences and growth
Comprehensive benefits including health insurance, dental, enhanced maternity and paternity leave, retirement or pension where applicable, access to therapists, wellbeing partnerships, team socials and more