2 months ago
Toronto, CanadaMid Level
Base Salary
$124k - $155k/yr
Responsibilities
- Build and maintain pipelines that ingest rosbags, sensor logs, and telemetry from the fleet.
- Convert field data into curated, versioned datasets and own dataset storage, indexing, querying, and delivery.
- Set up training workflows and optimize cloud infrastructure 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 AWS cloud storage and compute services.
- Understanding of ML workflows and dataset versioning.
- At least 2 years of MLOps or data infrastructure experience is preferred, ideally in robotics or autonomous systems.
- Experience with Weights & Biases, rosbag data, and large-scale sensor datasets is preferred.
- Working knowledge of C/C++ and experience supporting perception or ML research teams are preferred.
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.