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Software Engineer, ML Ops

Toronto · Toronto, Ontario, Canada

Live, first seen by us 76 days ago
Pay
Pay not listed
Work setting
Remote — work setting source
Location type: Remote
From the employer’s posting
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
Engineering — team source
Department: Engineering
From the employer’s posting

What you’ll work on

Full posting
  • Build and maintain pipelines that ingest rosbags, sensor logs and telemetry from the fleet

  • Convert raw field data into curated, versioned datasets and manage their storage and querying

  • Set up training workflows and optimize cloud costs

  • Build tooling for fast data access, reproducible experiments and automated evaluation

  • Generate metrics and diagnostics on dataset health, model performance and pipeline reliability

From the employer’s posting
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
Education & alternatives
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
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

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

Apply at AeroVect

Posting record

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Status in our records
Live
First seen by us
Aug 21, 202676 days ago
Recorded sightings
76
Last seen by us
Nov 5, 2026

These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.

How this job compares

Time since we first saw it

Day 76

Up longer than most. Similar jobs usually come down between day 6 and day 70.

From 4,444 similar postings that came down. Coming down is not always a hire.

AeroVect is hiring

1 open job

Open jobs by the week we first saw them, last 12 weeks.

Hiring record

See how this role fits your experience

Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.

  • C
  • C++
  • Python
  • AWS
  • Docker
  • S3
Where the posting names them
- Experience with Weights & Biases, rosbag data, and large-scale sensor datasets - Working knowledge of C/C++ - Experience supporting perception or ML research teams
- 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.)

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Demand for ML Engineer roles

New ML Engineer postings at the employers we follow are up 12% over the last 5 weeks compared with the 5 before.

Weekly new ML Engineer postings at the same employers, from the week of August 17 to the week of October 26. The fewest in a week was 625, the most 1,094, and the latest week had 876.
August 17Last week

Each bar is one week of new postings. The darkest bars are the last 5 weeks.

Counted from the hiring pages we’ve followed for at least five weeks, so employers we add don’t look like growth. Updated weekly.

About the role

We file this job under ML Engineer, by the work the posting describes.

ML engineers put machine learning models into products. They write the code that trains, ships, serves and monitors models so a recommendation or prediction works for real users.

Postings ask for strong Python and software engineering, a framework such as PyTorch, cloud services, and more and more often experience with large language models.

A data scientist often works out which model to build; an ML engineer makes it run reliably in production.

US government figures for computer and information research scientists

Median yearly pay, May 2025
$140,300
Expected change, 2025 to 2035
21.8% more jobsagainst 3.5% for all jobs

The government has no code for ML engineers, so these figures are for the closest group, computer and information research scientists.

Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1221.

Job description

View original posting ↗

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

Source details

View original posting ↗

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Pay

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Location & working pattern

Toronto, Ontario, Canada

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