Software Engineer, ML Ops

AeroVect Technologies Inc.; Toronto; On-site; CAD 110,000 - 150,000; Full time

Job summary

AeroVect Technologies Inc. is seeking a data engineer to build and maintain data pipelines, transforming raw sensor data into curated, versioned datasets for our perception team. You will manage storage, indexing, and dataset vending while optimizing training workflows and cloud costs.

The role emphasizes strong Python, ROS2, and DevOps proficiency, with familiarity in AWS services and ML workflow tools to support large-scale autonomous systems projects in Toronto.

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.).
• Understanding of ML workflows and dataset versioning.

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.
• Generate metrics and diagnostics to track dataset health, model performance, and pipeline reliability.

Skills

Python

ROS2

Docker

AWS (S3, EC2)

ML workflows

Dataset versioning

C/C++

Weights & Biases

Education

Bachelor's or Master's in Computer Science, Robotics, Data Engineering

Tools

Weights & Biases

ROS tooling

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