LiDAR Characterization & Perception Data Engineer - Mountain View, CA

Originally posted 30 June 2026 by the employer.

Build Python and C++ data pipelines while characterizing 4D LiDAR sensor performance across customer vehicle deployments.

About the role

This role bridges hardware, customer integration (FAE), and perception teams to manage the lifecycle of sensor data in the field. You will split time between characterizing physical sensor performance, supporting customer deployments, and building production-grade Python and C++ data pipelines to ingest, validate, and label data for perception models.

What you'll do

- Act as a technical liaison for customers, assist with hardware integration, and characterize 4D LiDAR performance—including range, velocity, and point cloud quality—in real-world environments. - 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. - Run camera, LiDAR, and GPS calibration workflows on collection vehicles and customer platforms, debugging integration issues such as sensor connectivity, logging failures, and network dropouts. - Build and maintain ETL pipelines moving high-volume sensor data to internal storage, collaborate with annotation vendors to package data, and validate returned labels for the perception team. - Collaborate with operations and customer engineering teams to plan, support, and execute data collection runs.

What you'll need

- 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 (or 2+ years with a Master's). - Hands-on experience with LiDAR, radar, or camera systems, including hardware troubleshooting, calibration, and point cloud analysis. - Fundamentals in software engineering (data structures, system design) and experience designing or operating data pipelines at scale. - Familiarity with robotics or autonomous systems data such as ROS, sensor logs, binary formats, or perception datasets. - Willingness to travel up to 20%.

Skills: LiDAR performance, hardware/systems engineering, sensor data, calibration workflows, data pipelines, sensor connectivity