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Software Engineer, ML Ops

Toronto · Toronto, Ontario, Canada

Pay
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Work setup
Remote — work setup source
Location type: Remote
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Employment
Full-time — employment source
Employment type: Full-time
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Team
Engineering — team source
Department: Engineering
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Apply at Aerovect

Tools in this posting

  • Python
  • AWS
  • Docker
  • S3
  • C++
  • C
Source — Tool mentions in context
- 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
- 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
- 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.)
- Experience with Weights & Biases, rosbag data, and large-scale sensor datasets - Working knowledge of C/C++ - Experience supporting perception or ML research teams

About Aerovect

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations.

In the employer’s words · Read in context

Job description

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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

Your next step

  • Have your CV and examples of relevant work ready.
  • Check the listed location, eligibility and core experience before starting.
  • Ask the employer about the salary range before committing time to the process.

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Pay

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Toronto, Ontario, Canada

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Status in our records
Active
First seen by us
Aug 21, 2026
Recorded sightings
37
Last seen by us
Sep 27, 2026

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