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Software Engineer, ML Ops

Role overview

Qualifications

  • 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.)

Responsibilities

  • 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

Key facts

Other skills

  • Teamwork
  • Problem Solving

About the company

AeroVect logo

AeroVect

Autonomous Vehicles & Self-Driving Tech

AeroVect deploys autonomous driving systems for GSE, trusted by the world's most innovative airlines and ground handlers.

Company details

Company typeStartup
IndustryAutonomous Vehicles & Self-Driving Tech
Company size11 - 50

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Job description

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

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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