Develop and maintain scalable data systems for sensor data, including ETL pipelines, hardware/software integration, and workflow collaboration.
About us:
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're looking for an Perception Data Engineer who can own data collection, scalable data systems, and sensor data workflows. You'll work cross-functionally with perception, operations, and labeling teams to build fast, reliable, and production-grade data pipelines.
What you will be doing
- Develop Python and C++ infrastructure to ingest, validate, and organize camera and LiDAR data from our collection vehicles — file handling, data verification, metadata extraction, and database writes.
- Run camera, lidar, gps calibration workflows on the data collection vehicles.
- Debug hardware/software integration issues on data collection rigs including sensor connectivity, logging failures, storage limits, and network dropouts
- Build and maintain ETL pipelines that move high-volume sensor data from vehicles to internal storage and annotation vendors
- Collaborate with external annotation and labeling vendors: package data for delivery, validate returned labels, and flag quality issues
- Collaborate with the operations team to plan, support, and execute data collection runs
What You Have
- Bachelor's degree in Computer Science, Electrical Engineering, or a related field; or equivalent practical experience
- 3+ years of industry experience in software development, with production Python and C++ (2+ years with a Master's)
- Strong fundamentals in software engineering — data structures, algorithms, system design, and writing code that is readable, testable, and maintainable
- Hands-on experience designing and operating data pipelines at scale, including ownership through incidents and iterations
- Familiarity with robotics or autonomous systems data — sensor logs, binary formats, or perception datasets is a plus
- Experience with databases as part of a production data workflow, including schema design and data integrity considerations
- Ability to work independently and cross-functionally in a fast-moving environment with ambiguous requirements
Top Skills
C++
Python
Aeva, Inc. Mountain View, California, USA Office
555 Ellis St, Mountain View, CA, United States
Similar Jobs
Automotive
Lead multi-year data strategy and architecture for Perception, drive cross-org technical decisions, establish governance and APIs, solve complex data problems (active learning, automated curation), and mentor senior engineers to scale ML data infrastructure and systems.
Top Skills:
BeamC++FlumePythonSpark
Artificial Intelligence • Automotive • Information Technology • Robotics
The role involves bridging machine learning and systems engineering to enhance autonomy performance by optimizing data quality and developing frameworks for synthetic data in autonomous systems.
Top Skills:
Autonomous SystemsC/C++MlPythonRobotics
Automotive
Design and enhance large-scale data pipelines for machine learning teams, ensuring high-quality dataset delivery and facilitating new model deployments.
Top Skills:
BeamC++DataflowPythonSpark
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
