Software Engineer, ML Ops (Robotics)

TL;DR

Software Engineer, ML Ops (Robotics): Build and maintain data pipelines to ingest field data from autonomous fleet with an accent on dataset curation, versioning, storage, and ML workflows. Focus on optimizing training workflows, developing tooling for perception engineers, and generating metrics for dataset health and pipeline reliability.

Toronto; Atlanta - Hybrid; Atlanta - Onsite

Company

Transforming ground handling with autonomy for airlines and ground service providers worldwide. Series A company backed by top-tier VCs in aviation and autonomous driving.

What you will do

• Build and maintain data pipelines to ingest field data (rosbags, sensor logs, telemetry) from fleet
• Convert raw data into curated, versioned datasets for perception team and manage storage, indexing, querying
• Set up training workflows and optimize cloud costs
• Build tooling to accelerate perception engineers' workflows including fast data access and automated evaluation
• Generate metrics and diagnostics for dataset health, model performance, and pipeline reliability

Requirements

• Bachelor's or Master's in Computer Science, Robotics, Data Engineering, or 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

Nice to have

• Master's in Computer Science, Robotics, or related
• 2+ years MLOps or data infrastructure experience in robotics/autonomous systems
• Experience with Weights & Biases, rosbag data, large-scale sensor datasets
• Working knowledge of C/C++
• Experience supporting perception or ML research teams