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Software Engineer, ML Ops

Build and maintain data pipelines to ingest field data and convert raw sensor logs into curated datasets for perception teams. Develop training workflows, optimize cloud costs, and create tooling to accelerate ML experiments and evaluation.

  • On-site
  • Toronto, ON
  • Posted Aug 21, 2026
  • Apply by Sep 20, 2026
  • 1 position

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Job summary

Search jobs Explore companies Join talent network Talent Software Engineer, ML Ops Aerovect Software Engineering, Operations, Data Science Toronto, ON, Canada Posted on Aug 21, 2026 Apply now 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 Apply now See more open positions at Aerovect

What you’ll do

Build and maintain data pipelines to ingest field data and convert raw sensor logs into curated datasets for perception teams. Develop training workflows, optimize cloud costs, and create tooling to accelerate ML experiments and evaluation.

Requirements

Requires a degree in Computer Science or Robotics with strong Python and ROS2 proficiency and knowledge of DevOps tools. Preference is given to candidates with 2+ years of MLOps experience in robotics or autonomous systems.

Listed skills

  • DockerPreferred
  • Amazon Web ServicesPreferred
  • C++Preferred
  • PythonPreferred

Other relevant skills

Identified from the job description. Confirm important requirements above.

  • Python
  • ROS2
  • Docker
  • AWS
  • MLOps
  • Data Engineering
  • C++
  • Dataset Versioning
  • Cloud Storage
  • Cloud Compute
  • Weights & Biases
  • Robotics

Job areas

  • Software
  • Engineering
  • Data & Analytics
  • Technology
  • Transportation

Additional details

Minimum education
Bachelor’s degree
Minimum experience
2+ years
Apply by
Sep 20, 2026
Posting language
English
Working hours
40 hours per week
Seniority
Entry level