Software Engineer, ML Ops
Build and maintain data pipelines to ingest field data and convert it into curated datasets for the perception team. Develop tooling to accelerate ML workflows, optimize cloud costs, and track model performance metrics.
- On-site
- Toronto, ON
- Posted Jul 17, 2026
- 1 position
Job summary
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
What you’ll do
Build and maintain data pipelines to ingest field data and convert it into curated datasets for the perception team. Develop tooling to accelerate ML workflows, optimize cloud costs, and track model performance metrics.
Requirements
Requires a degree in Computer Science, Robotics, or a related field with strong proficiency in Python and ROS2. Experience with Docker, AWS, and ML workflows is required, with a preference for 2+ years of MLOps experience in autonomous systems.
Benefits
• Equity
Other relevant skills
Identified from the job description. Confirm important requirements above.
- Python
- Ros2
- Docker
- Aws
- Mlops
- Data Engineering
- C++
- Dataset Versioning
- Cloud Storage
- Devops
- Pipelines
- MLOps (Machine Learning Operations)
- Workflow Management
- Data Access
- Data Version Control (DVC)
- C (Programming Language)
- Research
- Amazon Elastic Compute Cloud
- Amazon S3
- Autonomous System
- Management
- C++ (Programming Language)
- Venture Capital
- Computer Science
- Data Infrastructure
- DevOps
- Python (Programming Language)
- Machine Learning
- Operations
- Telemetry
- Robotics
- Tooling
- Data Pipelines
- Docker (Software)
Job areas
- Software
- Engineering
- Technology
- Data & Analytics
- Transportation
- Software Engineering Manager
- Machine Learning Engineer
- Software Developers
- Computer and Information Research Scientists
Additional details
- Minimum education
- Bachelor’s degree
- Minimum experience
- 2+ years
- Posting language
- English
- Working hours
- 40 hours per week