Software Engineer, ML Ops

Build and maintain data pipelines to ingest field data (rosbags, sensor logs, telemetry) from our fleet

Convert raw field data into curated, versioned datasets for the perception team and own dataset management - storage, indexing, querying, and vending datasets

Set up training workflows and optimize cloud costs

Build tooling to accelerate perception engineers' workflows - fast data access, reproducible experiments, automated evaluation pipelines

Generate metrics and diagnostics to track dataset health, model performance, and pipeline reliability

Bachelor's or Master's degree in Computer Science, Robotics, Data Engineering, or a related field

Strong Python proficiency and working knowledge of ROS2

Working knowledge of docker and other DevOps tools

Familiarity with cloud storage and compute (AWS - S3, EC2, etc.)

Understanding of ML workflows and dataset versioning

Master's in Computer Science, Robotics, or a related discipline

2+ years of MLOps or data infrastructure experience, ideally in robotics or autonomous systems

Experience with Weights & Biases, rosbag data, and large-scale sensor datasets

Working knowledge of C/C++

Experience supporting perception or ML research teams