Time since we first saw it
Day 76
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From 4,442 similar postings that came down. Coming down is not always a hire.
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 postingBuild 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
Posting record
Report an error- 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
AeroVect is hiring
1 open job
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee 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.)
Your next step
Complete your application on jobs.ashbyhq.com. The employer’s form will show what is required.
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- No account needed. “Autofill from resume” at the top of the form fills the key fields from your file.
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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.
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
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
Source notes
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- Pay
No pay amount identified in the saved description.
- Location & working pattern
Toronto, Ontario, Canada
Working pattern and location restrictions need checking in the full posting.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.