We're working with a leading enterprise committed to advancing healthcare through innovative research and technological solutions, focusing on developing a global imaging platform.
The Role
- Build and support ML / MLOps capabilities within the Global Imaging Platform
- Integrate ML models and workflows with IDPs, ARDs, App Catalog, and model registry
- Support SageMaker integration as the primary algorithm development environment
- Package algorithms for repeatable execution, versioning, lineage, and auditability
- Implement model metadata, version control, experiment tracking, and reproducible build patterns
- Support in-platform inferencing workflows for SageMaker-hosted or connected models
What You'll Need
- Strong hands-on experience with Python and ML engineering libraries
- Experience with AWS SageMaker, model deployment, and endpoint / inference workflows
- Experience with MLOps, model registry, experiment tracking, model versioning, and reproducibility
- Knowledge of CI/CD pipelines for ML model packaging, deployment, and promotion
- Familiarity with GxP-ready workflows and validation evidence generation
What's On Offer
- Opportunity to work on a global imaging platform with significant impact
- Collaborate with architects, data scientists, and subject matter experts
- Contribute to the advancement of life sciences through cutting-edge ML engineering
Apply via Haystack today!
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ML Engineer
Haystack
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