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Software Engineer, ML Ops

AeroVect · Toronto · Remote

  • Transportation & Logistics
  • 51–200 employees
  • South San Francisco, California

Mixed hiring record · median 30 days open

100100

Hiring signal

Actively hiring

Posted today · still listed on the employer's own board · How we score

All reasons
  • 28% of this employer's openings are over 60 days old

In its favour

  • Posted today
  • Still listed on the employer's own board

Did you apply?

Software Engineer, ML Ops at AeroVect. We’ll keep it in your applied jobs, so you can see it later and be warned before applying to the same employer twice.

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

Skills

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