System Soft Technologies provided pay range This range is provided by System Soft Technologies. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more. Base pay range $75.00/hr - $80.00/hr 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: Bachelor’s degree in Computer Science, Artificial Intelligence, Informatics, or a closely related field. Master’s degree is a plus. Minimum of 3 years of relevant experience as a Machine Learning Engineer. Proven expertise in deploying and maintaining machine learning models in production environments. Strong knowledge of healthcare industry standards, regulations, and systems, including experience integrating ML models with Electronic Health Records (EHR) systems. Proficiency in cloud platforms such as AWS, GCP, or Azure for building scalable ML infrastructures. Skilled in containerization technologies such as Docker and Kubernetes. Strong understanding of security and compliance standards for machine learning systems. Experience with version control systems to track changes in ML models and associated code. Certifications in machine learning or related fields- a big plus. Seniority level Mid-Senior level Employment type Contract Job function Information Technology and Health Care Provider Industries IT Services and IT Consulting #J-18808-Ljbffr System Soft Technologies
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