Characterize next-generation 4D LiDAR sensors through laboratory and vehicle testing, field data collection, automated test development, system-level debugging, calibration verification, and sensor data analysis. The role involves investigating issues across hardware, firmware, and software while collaborating with optics, algorithms, hardware, and systems engineering teams. Results will be documented and presented to cross-functional stakeholders.
Aeva’s mission is to bring the next wave of perception to a broad range of applications from automated driving to industrial robotics, consumer electronics, consumer health, security, and beyond. Aeva is transforming autonomy with its groundbreaking sensing and perception technology that integrates all key LiDAR components onto a silicon photonics chip in a compact module. Aeva 4D LiDAR sensors uniquely detect instant velocity in addition to 3D position, allowing autonomous devices like vehicles and robots to make more intelligent and safe decisions.
Role Overview
We are looking for a Systems Engineer, LiDAR Characterization, to join the Systems team and work hands-on with our next-generation 4D LiDAR sensors. This role is for someone who wants to spend most of their time on the sensor itself: running it in the lab and in the field, measuring how it performs, and working out why it behaves the way it does.
You will characterize sensor performance across a wide range of scenarios, debug system-level issues, and support sensor calibration. You will work closely with senior systems engineers and with the algorithms, firmware, hardware, and optics teams, and you will build a working understanding of the full sensor, from the photonics and electronics through signal processing to the point cloud.
What you'll do
- Set up and run tests on LiDAR sensors in the lab and on vehicles for comprehensive characterization
- Develop automation software to accelerate lab testing and data collection
- Support field data collection across real-world scenarios, including preparing sensors and test setups and logging test conditions.
- Investigate system-level issues: reproduce the problem, collect diagnostic data, and work with the relevant engineering teams to find the root cause.
- Help develop, run, and verify sensor calibration procedures.
- Analyze sensor data with Python or MATLAB, and document and present results to the Systems team and cross-functional partners.
What you'll have
- An MS in Electrical Engineering, Physics, Optics/Photonics, Mechanical Engineering, or a related field, with 0–2 years of industry experience.
- Hands-on lab experience with sensors, optical systems, or electronic test equipment from research, internships, or industry.
- Proficiency in Python or MATLAB for data analysis, and a foundation in signal processing, optics, or measurement statistics.
- A methodical approach to debugging problems that span hardware, firmware, and software, and clear written and verbal communication.
- Experience with LiDAR, radar, or other perception sensors, FMCW or coherent detection, or sensor calibration is a plus.
What's in it for you
- Spend most of your time hands-on with a cutting-edge 4D LiDAR sensor and learn the full system end to end.
- Work alongside and be mentored by experienced systems, optics, and signal processing engineers.
- Be part of a fast-paced and dynamic team.
Aeva, Inc. Mountain View, California, USA Office
555 Ellis St, Mountain View, CA, United States
Similar Jobs
Cloud • Information Technology • Consulting
Owns strategic enterprise client relationships for managed and professional services, driving account growth, retention, revenue expansion, and customer outcomes. Leads executive engagement, strategic account planning, complex multi-year sales cycles, forecasting, and cross-functional coordination across sales, engineering, delivery, product, and leadership teams. Serves as the primary relationship owner and executive escalation point while aligning cloud and technology solutions to client business objectives.
Top Skills:
AWSGCPHybrid CloudAzurePrivate CloudPublic CloudVMware
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Lead technical pre-sales engagements for large LATAM enterprise customers. Partner with account teams and channel partners, conduct Spanish-language discovery sessions and demonstrations, advocate for Atlassian Rovo and Teamwork Graph, architect customized solutions, and translate complex business challenges into measurable customer value. Build executive relationships, influence cross-functional teams, provide market feedback to Product Management, and support complex, high-stakes enterprise deals.
Top Skills:
Artificial IntelligenceAtlassian RovoCloud Software PlatformsTeamwork Graph
Cloud • Information Technology • Productivity • Security • Software • App development • Automation
Develops core AI capabilities for Atlassian’s DevAI products, including LLM-based methodologies, prompt engineering, end-to-end AI features, data preprocessing, feature engineering, experimentation, model evaluation, pipeline optimization, and monitoring. Collaborates with data scientists, software engineers, and cross-functional partner teams to solve complex problems and apply advances in machine learning and AI.
Top Skills:
Feature EngineeringLarge Language Models (Llms)Machine LearningMachine Learning PipelinesPrompt Engineering
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
