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Software Engineer, ML Ops

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Software Engineer, ML Ops in Canada

  • AeroVect
  • Full time
  • Email
  • Toronto

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.

Salary: $124k - $155k/yr

AeroVect

AI-powered airport logistics automation solutions, trusted by the world's largest airlines and airports.

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