Software Engineer, ML Ops
Toronto · Toronto, Ontario, Canada
- Pay
- Salary not listed in the saved posting
- Work setup
Remote — work setup 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
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
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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Source & posting history
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.
- Status in our records
- Active
- First seen by us
- Aug 21, 2026
- Recorded sightings
- 37
- Last seen by us
- Sep 27, 2026
These dates show when we found the listing. Check the employer’s website to confirm it is still accepting applications.
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