Posted 2 hours ago
Software Engineer, ML Ops
@ AeroVect
Toronto, Ontario
Overview
AeroVect is hiring a full-time Software Engineer for ML Ops to build data pipelines and dataset tooling for its autonomous ground handling fleet. The role covers ingesting field sensor data, curating versioned datasets, and optimizing training workflows on the cloud. The position is based onsite in Toronto.
Responsibilities:
- Build and maintain data pipelines for fleet field data
- Convert raw data into versioned, curated datasets
- Set up training workflows and optimize cloud costs
- Build tooling for perception engineers' workflows
- Generate metrics and diagnostics for datasets and pipelines
Requirements summary:
- Bachelor's or Master's in computer science, robotics or related field
- Strong Python proficiency and working knowledge of ROS2
- Working knowledge of Docker and DevOps tools
- Familiarity with AWS cloud storage and compute
- Understanding of ML workflows and dataset versioning
Tools & skills
Source and dates
Employer career site / ATS feed · ashby
- Employer posting date
- 2026-11-06
- First seen by our source
- 2026-11-06
- Source record updated
- 2026-11-06
These dates describe the source record, not a live verification that the employer is still hiring. Check the original posting.
Job details
| Seniority | Mid level |
| Department | Software development |
| Hours per week | 40 (estimated) |
| Work setting | Office |
| Position | Mostly sitting |
| Physical demands | physical low · computer high |
| Languages | English |
| Education | Bachelor’s degree (required), Master’s degree (preferred) |
| Fields of study | Computer Science, Robotics, Data Engineering |
Summary and details written by AI from the posting; the employer’s posting is the authority.
AeroVect
Saved company profile
Historical company information from a saved The Jobs API profile (LinkedIn/Crunchbase fields). It is not live-verified; figures may have changed. Missing values remain unknown.
The Airport Automation Company
Full company description
AI-powered airport logistics automation solutions, trusted by the world's largest airlines and airports.
- LinkedIn followers
- 5,376
- People associated on LinkedIn
- 63
- Reported office locations
- 233 E Harris Ave, South San Francisco, California 94080, US
- Toronto, Ontario, CA
- Atlanta, Georgia 30308, US
- Frankfurt, DE
- New York, 10007, US
- Business categories
- Air Transportation
- Robotics
- Software
- Logistics
- Transportation
- Artificial Intelligence (AI)
- Aerospace
- Autonomous Vehicles
- Manufacturing
- Other recorded names
- AeroVect
- Specialties
- Aviation
- Autonomous Driving
- Aerospace
- Transportation
- Logistics
- Airport Automation
- Physical AI
- and Artificial Intelligence
- Profile identifies a recruitment agency
- No
- Reported total investment
- 27,000,000
Currency and observation date were not supplied; this is not a current valuation or a funding round.
AI-powered airport logistics automation solutions, trusted by the world's largest airlines and airports.
| Field | Value |
|---|---|
| Industry | Airlines and Aviation |
| Company size | 51-200 employees |
| Headquarters | South San Francisco, California |
| Organization type | Privately Held |
| Year founded | 2020 |
| Specialties | AviationAutonomous DrivingAerospaceTransportationLogisticsAirport AutomationPhysical AIand Artificial Intelligence |
| Open jobs on Jobsy | 16 |
| View page |
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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