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 - Solid 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

📌 Software Engineer, ML Ops (Toronto)
🏢 AeroVect Technologies
📍 Toronto