MLOps Engineer

Largeton Group is seeking a skilled MLOps Engineer with healthcare experience to build and manage scalable machine learning systems. The role involves working closely with Data Science and DevOps teams to deploy, monitor, and maintain ML models used in healthcare applications, ensuring compliance, data security, and high reliability.

Responsibilities:

• Build and maintain end-to-end ML pipelines (data ingestion → training → deployment → monitoring) for healthcare data
• Deploy ML models using CI/CD pipelines in production environments
• Work with Data Scientists to productionize models related to clinical, claims, or patient data
• Design scalable cloud infrastructure for ML workloads
• Monitor model performance, drift, and system reliability
• Ensure compliance with healthcare regulations (HIPAA or similar)
• Maintain data quality, privacy, and governance standards
• Automate model retraining and versioning workflows
• Optimize system performance and infrastructure cost
• Troubleshoot production issues and ensure system uptime

Requirements:

• Bachelor's/Master's in Computer Science, Data Science, or related field
• 7+ years of experience in MLOps / ML Engineering / DevOps
• Experience working with healthcare data (EHR, claims, EMR, etc.)
• Strong Python programming skills
• Experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn)
• Hands-on with CI/CD tools (Jenkins, GitHub Actions, GitLab CI)
• Experience with Docker and Kubernetes
• Cloud experience (AWS / Azure / GCP)
• Experience with data pipelines (Airflow, Kafka, Spark)
• Familiarity with MLflow / DVC for model versioning
• Experience in healthcare analytics or clinical data systems
• Knowledge of healthcare compliance standards (HIPAA, HL7, FHIR)
• Experience with real-time ML systems
• Familiarity with monitoring tools (Prometheus, Grafana)
• Understanding of data engineering concepts and distributed systems