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

Software Engineer, ML Ops

Similar jobs

Explore related jobs