1 day ago
Toronto, CanadaMid Level
Base Salary
$124k - $155k/yr
Responsibilities
- Build and maintain pipelines ingesting rosbags, sensor logs, and telemetry from the company’s fleet.
- Convert raw field data into curated, versioned datasets and own dataset storage, indexing, querying, and vending.
- Set up training workflows and optimize cloud costs.
- Build tooling for fast data access, reproducible experiments, and automated evaluation pipelines.
- Generate metrics and diagnostics for dataset health, model performance, and pipeline reliability.
Requirements
- 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, including AWS services such as S3 and EC2.
- Understanding of ML workflows and dataset versioning.
- Preferred: master’s degree in Computer Science, Robotics, or a related discipline.
- Preferred: 2+ years of MLOps or data infrastructure experience, ideally in robotics or autonomous systems.
- Preferred: experience with Weights & Biases, rosbag data, large-scale sensor datasets, C/C++, and supporting perception or ML research teams.
Benefits
- The role is based onsite in Toronto.
Categories
Data EngineeringML Engineering
About AeroVect
AeroVect builds autonomous driving systems and software to automate airport ground service equipment, improving ramp logistics for airlines, airports, and ground handling providers. It deploys and supports autonomy for fleets used by major carriers and ground service companies. Founded in 2020 and headquartered in South San Francisco, it is a privately held Series A company.