What are the responsibilities and job description for the Machine Learning Engineer- Healthcare position at System Soft Technologies?
Summary
We are seeking a Machine Learning Operations Engineer with strong experience in the healthcare industry and expertise in deploying and maintaining production-grade machine learning models. The ideal candidate will have a deep understanding of healthcare standards, regulations, and electronic health record (EHR) systems. This role requires technical proficiency in machine learning pipelines, cloud platforms, and compliance standards, as well as a proven ability to collaborate with cross-functional teams to drive innovation in healthcare AI solutions.
Responsibilities :
- ML Model Deployment & Optimization : Deploy, maintain, and scale production-grade machine learning models to ensure real-time inference, reliability, and scalability.
- Pipeline Development : Create and optimize end-to-end AI pipelines, including data ingestion, preprocessing, search, and retrieval processes.
- CI / CD Integration : Build and maintain CI / CD pipelines for machine learning models, automating testing, and deployment processes.
- Monitoring & Logging : Implement monitoring and logging solutions to track model performance, system health, and detect anomalies.
- Collaboration & Leadership : Lead engineering efforts for ML / GenAI model development, large language model (LLM) advancements, and deployment frameworks in alignment with business strategies. Collaborate with data scientists, data engineers, and DevOps teams to achieve project goals.
- Compliance & Security : Ensure all systems meet healthcare-related security and compliance standards, including data protection and privacy regulations.
- Documentation : Maintain clear and comprehensive documentation of ML Ops processes, workflows, and configurations.
Qualifications :
