Sobre este puesto de LiDAR Characterization & Perception Data Engineer - Mountain View, CA en Aeva
What you will be doing
Sensor Characterization & FAE Support: Act as a technical liaison for customers. Assist with hardware integration and characterize 4D LiDAR performance (range, velocity, point cloud quality) in real-world environments to ensure optimal sensor deployment.
Data Infrastructure: Develop Python and C++ infrastructure to ingest, validate, and organize data from collection vehicles and customer fleets: handling file verification, metadata extraction, and database writes.
Calibration & Field Debugging: Run camera, LiDAR, and GPS calibration workflows on internal data collection vehicles and customer platforms. Debug hardware/software integration issues including sensor connectivity, logging failures, and network dropouts.
Pipelines & Labeling: Build and maintain ETL pipelines that move high-volume sensor data to internal storage. Collaborate with external annotation vendors to package data for delivery, validate returned labels, and flag quality issues for the perception team.
Operations Execution: Collaborate with operations and customer engineering teams to plan, support, and execute comprehensive data collection runs.
What You Have
Bachelor's degree in Computer Science, Electrical Engineering, Optics, or a related field; or equivalent practical experience.
3+ years of industry experience blending software development (production Python and C++) with hardware/systems engineering (2+ years with a Master's).
Hands-on experience with LiDAR, radar, or camera systems, including hardware troubleshooting, calibration, and point cloud analysis.
Strong fundamentals in software engineering (data structures, system design) and experience designing or operating data pipelines at scale.
Excellent communication skills, with the ability to translate complex technical issues between external customers, hardware engineers, and perception software teams.
Familiarity with robotics or autonomous systems data such as ROS, sensor logs, binary formats, or perception datasets is a strong plus.
Ability to work independently and cross-functionally in a fast-moving environment with ambiguous requirements.
