About the role
Who We Are
AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.
You will
- 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
You have
- 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
We Prefer
- 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
Please note this role will be based onsite in Toronto