Machine Learning Engineer

Working with a leading innovator in healthcare information systems, this company is transforming patient care through advanced technology. They are seeking passionate engineers to drive the development of AI-powered solutions that enhance the reliability and scalability of critical healthcare platforms.The Role Build and maintain CI/CD pipelines for machine learning, focusing on automated testing, model deployment, and version control. Deploy ML models as scalable APIs and microservices, ensuring performance and latency for clinical use. Implement monitoring tools to track model performance, data drift, and system health in production. Develop and optimize ETL processes to transform healthcare data (FHIR, HL7) into clean, usable datasets. Help build and maintain feature stores and data layers, ensuring consistency between training and production. Use Docker and Kubernetes to package and orchestrate ML workloads, adhering to security and compliance standards like HIPAA and HITRUST.What You'll Need Bachelor's or Master's degree in Computer Science, Software Engineering, Data Engineering, or a related field. 3-5 years of professional experience in software or data engineering, with at least 2 years focused on ML production environments. Strong proficiency in Python and familiarity with SQL; knowledge of Go or Java is a plus. Hands-on experience with a major cloud provider (AWS, Azure, or Google Cloud Platform) and Docker. Familiarity with ML libraries (PyTorch or Scikit-learn) and MLOps tools (e.g., Airflow, Prefect, BentoML, Kubeflow). Experience with data processing frameworks like Pandas, Spark, or dbt.What's On Offer Opportunity to make a significant impact on healthcare through AI innovation. Work in a dynamic environment focused on MLOps, data reliability, and production stability. Contribute to secure and scalable AI services within critical healthcare applications. Exposure to cutting-edge technologies like LLMs and frameworks like LangChain.Apply via Haystack today!