Software Engineer, ML Ops
Full-time
AeroVect
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.
Vacancy posted 3 days ago
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