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Software Engineer, ML Ops

AeroVect • Autonomous Driving • Air Transport • Bachelor's Degree • Python • C++ • 2 months ago
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Salary
$88k – $109k per year
Location
Remote (Toronto, Canada)
Seniority
Junior · 2+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 16, 2026. First seen by Alion on Aug 20, 2026. AeroVect scores B on the Alion truth index.

Overview
Company
Impact
Profile match

AeroVect

AeroVect is an autonomous driving technology company founded in 2020 that develops the AeroVect Driver, a self-driving software and sensor kit that automates airport ground support equipment such as baggage tractors and cargo haulers. Its systems are deployed with airlines and ground handlers at passenger and cargo hubs, and it hires motion planning and localization engineers, operations safety leads and autonomous vehicle test drivers in Atlanta, Toronto and New York. The company is headquartered in South San Francisco, California, United States.
aerovect.com • HQ: South San Francisco, United States • Air Transport • Autonomous Driving • 201-500 employees • Est. 2020
Tech stack of AeroVect
Backed by Soma Capital, Scribble Ventures, Nava Ventures

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

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