ML Ops Engineer - Data Pipelines & Perception Tooling

Outsiders Fund; Toronto; On-site; CAD 90,000 - 150,000; Full time

Job summary

AeroVect in Toronto is hiring a data engineer to build and maintain data pipelines for field data (rosbags, sensor logs, telemetry) and to curate versioned datasets for the perception team.

You will set up training workflows, optimize cloud costs, and build tooling for fast data access and reproducible experiments, while tracking dataset health and model performance.

On-site Toronto, with strong Python, ROS2, Docker and AWS skills; ML workflow and dataset versioning experience preferred.

Qualifications

• Bachelor's or Master's in CS, Robotics, Data Eng, or related field.
• Strong Python proficiency and ROS2 knowledge.
• Experience with Docker and cloud storage (AWS).
• Familiarity with ML workflows and dataset versioning.
• Nice to have MLOps or data infra in robotics environments.

Responsibilities

• Build and maintain data pipelines to ingest field data (rosbags, sensor logs, telemetry).
• 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

ML workflows

Dataset versioning

Cloud concepts

C/C++

Education

Bachelor's or Master's degree in Computer Science, Robotics, Data Engineering, or a related field

Tools

Docker

Weights & Biases

AWS

Job description

AeroVect in Toronto is hiring a data engineer to build and maintain data pipelines for field data (rosbags, sensor logs, telemetry) and to curate versioned datasets for the perception team.

You will set up training workflows, optimize cloud costs, and build tooling for fast data access and reproducible experiments, while tracking dataset health and model performance.

On-site Toronto, with strong Python, ROS2, Docker and AWS skills; ML workflow and dataset versioning experience preferred.