Software Engineer, ML Ops
Offre en anglaisYou will build and maintain data pipelines to ingest and curate field data from the fleet while optimizing cloud costs. Additionally, you will develop tooling to accelerate perception workflows and generate metrics to track model performance and dataset health.
- Sur place
- Toronto, ON
- Publié 20 août 2026
- 1 poste
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Résumé du poste
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
Ce que vous ferez
You will build and maintain data pipelines to ingest and curate field data from the fleet while optimizing cloud costs. Additionally, you will develop tooling to accelerate perception workflows and generate metrics to track model performance and dataset health.
Exigences
Candidates must have a Bachelor's or Master's degree in Computer Science, Robotics, or a related field with strong Python proficiency. Experience with ROS2, Docker, cloud infrastructure, and MLOps practices is required, with a preference for candidates having 2+ years of relevant experience.
Avantages
• Equity
Compétences indiquées
- DockerSouhaitée
- Amazon Web ServicesSouhaitée
- C++Souhaitée
- PythonSouhaitée
Autres compétences pertinentes
Relevées dans la description du poste. Confirmez les exigences importantes ci-dessus.
- Python
- ROS2
- Docker
- DevOps
- AWS
- S3
- EC2
- MLOps
- Data Engineering
- Data Pipelines
- Dataset Management
- Cloud Storage
- Cloud Compute
- C++
- Sensor Data
- Pipelines
- MLOps (Machine Learning Operations)
- Workflow Management
- Data Access
- Data Version Control (DVC)
- C (Programming Language)
- Research
- Amazon Elastic Compute Cloud
- Amazon S3
- Autonomous System
- Management
- C++ (Programming Language)
- Venture Capital
- Computer Science
- Data Infrastructure
- Python (Programming Language)
- Machine Learning
- Operations
- Telemetry
- Robotics
- Tooling
- Docker (Software)
Domaines d’emploi
- Software
- Engineering
- Technology
- Data & Analytics
- Transportation
- Software Engineering Manager
- Machine Learning Engineer
- Software Developers
- Computer and Information Research Scientists
Renseignements supplémentaires
- Formation minimale
- Baccalauréat
- Expérience minimale
- 2+ ans
- Langue de l’offre
- anglais
- Heures de travail
- 40 heures par semaine
- Exigences de lieu
- Country, Canada