Machine Learning Engineer
Core
Design, build, and deploy production-grade machine learning models for clinical decision support, early-warning alerts, patient-flow optimisation, and medication safety workflows.
Role type
Senior IC machine learning engineer (healthcare)
Builds
Production ML models powering clinical decision support and operational optimisation
Domain
Healthcare + Machine Learning
Deliverable
production ML models
Required skills
Python, PyTorch, TensorFlow, JAX, scikit-learn, MLflow, Kubeflow, Vertex AI, SageMaker, AWS, GCP, Azure
Preferred skills
Healthcare data, EHRs, HL7, FHIR, DICOM, clinical NLP, LLMs, foundation models, generative AI, clinical safety regulations
Technologies
PyTorch, TensorFlow, JAX, scikit-learn, MLflow, Kubeflow, Vertex AI, SageMaker, AWS, GCP, Azure
Responsibilities
Design, train, and deploy production machine learning models for clinical and operational use cases; Build reliable ML pipelines and support MLOps best practices; Work with clinicians, data scientists, and software engineers to translate healthcare problems into robust model-driven products; Support explainability, clinical safety, and regulatory readiness for AI-enabled features; Optimise model latency, cost, reliability, and scalability across cloud infrastructure; Contribute to the technical direction of the Greencube AI platform.
Seniority
Senior, hands-on IC
