ML/Data Infrastructure Engineer

pYou will build and operate the data and ML infrastructure that turns drone-collected data into deployable machine-learning capabilities. /p h3Your tasks /h3 ul liOwn infrastructure and workflows for ML data pools and datasets, from ingestion to versioning /li liHost in-house labeling tools and manage annotation workflows with external partners /li liAutomate and maintain infrastructure for ML training, evaluation and experiment tracking /li liBuild tooling and automation to move models from training to reliable deployment /li liMonitor training and model performance and feed production data back into development /li liProvide tools, documentation and workflows enabling engineers to go from data to deployable models /li /ul h3What you bring /h3 ul li3+ years of experience in data engineering, MLOps, ML infrastructure or related software engineering /li liStrong Python and software engineering skills with production-grade systems experience /li liHands-on experience with data storage, databases and large-scale data processing /li liPractical experience with AWS, particularly S3 and cloud-based compute and storage /li liExperience with ML lifecycle: versioning, experiment tracking, training orchestration, model registries or ML CI/CD /li liExperience with Docker, CI/CD, workflow orchestration or infrastructure-as-code /li liProficiency in English; French is a plus /li /ul h3Conditions /h3 ul liWorkload: 100 % /li liWork model: Hybrid /li liOption of a permanent position after the assignment if both sides want it /li /ul h3What to expect /h3 ul liFlexible schedules with option to work remotely up to 2 days per week /li li3-6 months interim, then a permanent position /li /ul h3Technologies /h3 ul liPython /li liAWS /li liS3 /li liDocker /li liMLflow /li liDVC /li liSageMaker /li /ul #J-18808-Ljbffr