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Software Engineer, ML Ops
Software Engineer, ML Ops
AeroVect is seeking a Software Engineer, ML Ops to build and maintain data pipelines for ingesting field data, curate versioned datasets, and optimize cloud-based training workflows. The role involves accelerating perception engineers' workflows and tracking dataset health and model performance.
About the role
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