Aerovect
Software Engineer, ML Ops
AeroVect is seeking an MLOps Software Engineer to build and maintain data pipelines, manage large-scale sensor datasets, and optimize training workflows for autonomous ground handling systems. The role involves developing tooling to support perception engineers using Python, ROS2, and cloud infrastructure.
- Compensation
- $123.8K–$154.8K / yr
- Location
- Toronto
- Work setup
- Remote
- Seniority
- Not specified
- Employment
- Not specified
- Experience
- 2+ years
- Category
- Devops
- Posted
Skills
Must have
- Bachelor's or Master's degree in Computer Science, Robotics, Data Engineering, or a related field
- Strong Python proficiency
- 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
Nice to have
- 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
Full 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 .
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