LiDAR Characterization & Perception Data Engineer - Mountain View, CA

Job Description

Job Description

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 a versatile engineer to serve as a critical bridge between our hardware, customer integration (FAE), and perception teams. As a shared resource, you will own the full lifecycle of our sensor data in the field. You will split your time between characterizing physical sensor performance, supporting customer deployments, and building the production-grade Python and C++ data pipelines required to ingest, validate, and label that data for our perception models.

• 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.

• 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.

Salary pay ranges are determined by role, level, and location. Within the range, the successful candidate’s starting base pay will be determined based on factors including job-related skills, experience, certifications, qualifications, relevant education or training, and market conditions. These ranges are subject to change in the future.   Depending on the position offered, equity, bonus, and other forms of compensation may be provided as part of a total compensation package, in addition to comprehensive medical, dental, and vision coverage, pre-tax commuter and health care/dependent care accounts, 401k plan, life and disability benefits, flexible time off, paid parental leave, and 11 paid holidays annually.

Aeva is an Equal Opportunity Employer including protected Veterans and individuals with disabilities.