Software Engineer, ML Ops
- Remote, Canada
Remote
$123,828 to $154,785 CAD / year · Full-time
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Job details
- Pay
- $123,828 to $154,785 CAD / year
- Job type
- Full-time
- Workplace
- Remote
- Remote eligibility
- Canada listed. Check the posting for province restrictions.
- Experience
- 2+ years of MLOps or data infrastructure experience, ideally in robotics or autonomous systems
- Posting language
- English
- Posted
Original 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
More about this job
Responsibilities
You will build and maintain data pipelines to ingest and curate field data while optimizing cloud costs and training workflows. Additionally, you will develop tooling to accelerate perception engineers' workflows and generate metrics to track model performance.
Requirements
The role requires a Bachelor's or Master's degree in Computer Science, Robotics, or a related field, along with strong Python proficiency. Candidates should have experience with ROS2, Docker, cloud storage, and MLOps practices.
Skills
- Python
- ROS2
- Docker
- DevOps
- AWS
- S3
- EC2
- MLOps
- Data infrastructure
- Weights & Biases
- Rosbag
- Sensor datasets
- C++
- Data pipelines
- Dataset management
Benefits
- Equity
Visa sponsorship
Not detected in the job text
Categories
- Software
- Engineering
- Data & Analytics
- Technology
- Logistics
Keywords
- Software Engineer
- ML Ops
- Autonomy
- Aviation
- Autonomous driving
- Data pipelines
- Rosbags
- Sensor logs
- Telemetry
- Perception
- Dataset management
- Cloud storage
- AWS
- S3
- EC2
- ML workflows
- Dataset versioning
- Robotics
- Data engineering
- Python
- ROS2
- Docker
- DevOps
- Weights & Biases
- C++
- Sensor datasets
- Model performance
- Pipeline reliability
Seniority
Mid level
Tools
- ROS2
- Docker
- AWS S3
- AWS EC2
- Weights & Biases
Languages
- English
Fields of study
- Computer Science
- Robotics
- Data Engineering