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Aerovect · Posted 2mo ago

Software Engineer, ML Ops

$123.8–154.8K/yrRemote
Location
🇨🇦 Toronto, Canada
Contract
Full-time
Role
ML engineering
Source
Employer’s own job board (Ashby)

Stack

  • S3
  • Weights & Biases
  • Python
  • C++
  • AWS
  • Docker

The posting

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 http://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