ML/Data Infrastructure Engineer

You will build and operate the data and ML infrastructure that turns drone-collected data into deployable machine-learning capabilities.

Your tasks

• Own infrastructure and workflows for ML data pools and datasets, from ingestion to versioning
• Host in-house labeling tools and manage annotation workflows with external partners
• Automate and maintain infrastructure for ML training, evaluation and experiment tracking
• Build tooling and automation to move models from training to reliable deployment
• Monitor training and model performance and feed production data back into development
• Provide tools, documentation and workflows enabling engineers to go from data to deployable models

What you bring

• 3+ years of experience in data engineering, MLOps, ML infrastructure or related software engineering
• Strong Python and software engineering skills with production-grade systems experience
• Hands-on experience with data storage, databases and large-scale data processing
• Practical experience with AWS, particularly S3 and cloud-based compute and storage
• Experience with ML lifecycle: versioning, experiment tracking, training orchestration, model registries or ML CI/CD
• Experience with Docker, CI/CD, workflow orchestration or infrastructure-as-code
• Proficiency in English; French is a plus

Conditions

• Workload: 100 %
• Work model: Hybrid
• Option of a permanent position after the assignment if both sides want it

What to expect

• Flexible schedules with option to work remotely up to 2 days per week
• 3-6 months interim, then a permanent position

Technologies

• Python
• AWS
• S3
• Docker
• MLflow
• DVC
• SageMaker