Machine Learning Engineer

A pioneering technology company is revolutionising healthcare through advanced AI solutions. They are dedicated to integrating cutting-edge machine learning into critical healthcare information systems to enhance patient care and operational efficiency.

The Role

• Build and maintain robust pipelines for AI in Healthcare Information Systems (HIS).
• Bridge the gap between data science and software engineering by implementing automated MLOps workflows.
• Deploy ML models as scalable APIs and microservices, ensuring performance and latency for clinical use.
• Develop and optimize ETL processes for transforming healthcare data (FHIR, HL7) into usable datasets.
• Implement monitoring tools to track model performance, data drift, and system health in production.
• Ensure data handling and deployments meet HIPAA and HITRUST security standards.

What You'll Need

• 3-5 years of professional experience in software or data engineering, with at least 2 years in ML production.
• Strong proficiency in Python; familiarity with SQL and compiled languages (Go/Java) is a plus.
• Hands-on experience with a major cloud provider (AWS, Azure, or GCP) and Docker/Kubernetes.
• Familiarity with ML libraries (PyTorch, Scikit-learn) and MLOps tools (Airflow, Prefect, BentoML, Kubeflow).
• Experience with data processing frameworks like Pandas, Spark, or dbt.
• Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or related field.

What's On Offer

• Opportunity to make a significant impact on healthcare through AI innovation.
• Work on complex MLOps, data reliability, and production stability challenges.
• Exposure to cutting-edge technologies like LLMs and frameworks like LangChain.
• Collaborative environment focused on engineering best practices and code quality.

Apply via Haystack today!