Software Engineer, ML Ops

Name: RiseMe
Availability: InStock

Toronto, ONOnsiteFull TimePosted 22 hours ago

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Required skills

data pipelines
field data
rosbags
sensor logs
telemetry
curated datasets
versioned datasets
dataset management
storage
indexing

Nice to have

robotics
autonomous systems
large-scale sensor datasets

Role summary

AeroVect is seeking a Software Engineer, ML Ops to build and maintain data pipelines, manage datasets, set up training workflows, and develop tooling for perception engineers. The role involves working with field data (rosbags, sensor logs, telemetry), optimizing cloud costs, and generating metrics for dataset health and model performance. Requires strong Python proficiency, working knowledge of ROS2, Docker, DevOps tools, cloud storage/compute (AWS), and ML workflows/dataset versioning. Familiarity with MLOps, data infrastructure, Weights & Biases, and C/C++ is preferred. This onsite role is based in Toronto.

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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