Machine Learning Engineer - Perception

United States·Mountain ViewFull-Timemid

Machine Learning EngineerData

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Quick Summary

Overview

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,

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Machine Learning EngineerData

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:

As an ML Engineer on our perception team, you will own the development and deployment of 3D perception models across object detection, semantic segmentation, and lane detection. Your work will directly shape how our autonomous systems perceive and understand the world.

Train and evaluate 3D perception models for object detection, segmentation, and lane detection

Improve model performance across challenging conditions such as long range and sparse point clouds

Deploy perception models to production and own the full lifecycle from research to real-world integration

Diagnose and resolve deployment issues including latency, accuracy degradation, and edge case failures in the field

Monitor model performance in production and iterate rapidly based on real-world feedback

Build auto-labeling pipelines using vision-language models to accelerate data annotation

MS or PhD in CS, Robotics, or a related field

Hands-on experience with 3D object detection on LiDAR point clouds

Experience using VLMs for auto-labeling or offline perception tasks

Strong Python and PyTorch skills

Familiarity with large-scale dataset pipelines and annotation workflows

Experience with multi-object tracking or sensor fusion is a plus