Software Engineer, ML Ops
AeroVect · Remote · Toronto ·
COMPENSATION
$124k – $155k
Listed on the employer's job board (Ashby)
- Onsite in Toronto
- Python + ROS2
- AWS Cloud
- MLOps Focus
- Series A Startup
Join AeroVect's engineering team to develop the infrastructure behind autonomous ground handling solutions. You will build systems that ingest field data from rosbags and sensor logs, converting them into curated datasets for the perception team. Your work will enable reproducible experiments and accelerate model development for airline operations.
What you'll do
- Build and maintain data pipelines for ingesting field data like rosbags and telemetry
- Convert raw data into versioned datasets with storage, indexing, and querying capabilities
- Set up training workflows and optimize cloud computing costs
- Develop tooling for fast data access and automated evaluation pipelines
- Generate metrics to monitor dataset health and model performance
What you'll need
- Bachelor's or Master's degree in Computer Science, Robotics, or Data Engineering
- Strong proficiency in Python and working knowledge of ROS2
- Familiarity with Docker and other DevOps tools
- Experience with cloud storage and compute services such as AWS S3 and EC2
- Understanding of machine learning workflows and dataset versioning
Nice to have
- Master's degree in a relevant technical discipline
- Two or more years of experience in MLOps or data infrastructure
- Background in robotics or autonomous systems
- Experience with Weights & Biases and large-scale sensor datasets
- Working knowledge of C/C++
- Experience supporting perception or machine learning research teams
Stack
- Python
- ROS2
- Docker
- AWS
- C/C++
- Weights & Biases
How you'll work
- Onsite position based in Toronto