Python ML Engineer (LLM Ops) - Healthcare Domain

Position Overview We are seeking a Python ML Engineer (LLM Ops) to design, build, and operationalize production-grade Machine Learning and Generative AI solutions. The ideal candidate will have hands-on experience with Python, LLMOps, Databricks, AWS, and NLP, along with a strong background in deploying scalable ML pipelines in cloud environments. Experience working with Healthcare data and HIPAA-compliant systems is essential. Position: Python ML Engineer (LLM Ops) Experience: 3–5 Years Location: Remote Duration: 6 Months Must-Have Skills • Python • Machine Learning Engineering (MLE) • LLMOps • Databricks • AWS • SQL • Natural Language Processing (NLP) • CI/CD Pipelines • Git • Recent Healthcare domain experience • PHI/HIPAA-compliant data handling • HL7 ADT message format knowledge Key Responsibilities • Design, develop, and deploy production-ready ML and LLM applications using Python. • Build scalable ML pipelines on Databricks and AWS. • Implement LLMOps for model deployment, monitoring, evaluation, and lifecycle management. • Develop cluster and job orchestration for large-scale data processing. • Build automated CI/CD pipelines for ML workloads. • Develop NLP solutions for structured and unstructured healthcare data. • Optimize scalable compute orchestration to improve performance. • Collaborate with architects, data engineers, and QA teams. Nice to Have • MLflow • Docker & Kubernetes • FHIR • Retrieval-Augmented Generation (RAG) • Vector Databases