{"schemaVersion":"jobsearcher.job.v1","id":"e4a58375b2a3ef3f3fdb2abe","url":"https://jobsearcher.com/jobs/e4a58375b2a3ef3f3fdb2abe","canonicalUrl":"https://jobsearcher.com/jobs/e4a58375b2a3ef3f3fdb2abe","title":"Machine Learning Operations Engineer","description":"The Machine Learning Operations (MLOps) Engineer is responsible for the full lifecycle management of machine learning models, including design, build, deployment, and maintenance. This role plays an integral part in implementing artificial intelligence solutions across Keck Medicine of USC, partnering with data scientists, engineers, and clinical operations teams to deliver scalable, reliable, and compliant AI solutions. The MLOps Engineer ensures seamless integration, automation, and monitoring of models within production environments, leveraging DevOps expertise to advance patient care, operational excellence, and clinical research.\r\nKey Responsibilities Design, build, deploy, and maintain machine learning models across production environments.\r\nPartner with data scientists, engineers, and clinical operations to implement AI solutions.\r\nDevelop and continuously improve MLOps pipelines for monitoring, versioning, and deployment.\r\nImplement best practices for testing, debugging, and performance monitoring of AI systems.\r\nEnsure seamless integration, automation, and scaling of AI solutions within existing infrastructure.\r\nSupport predictive modeling, large language models (LLMs), and natural language processing (NLP) initiatives.\r\nApply Retrieval-Augmented Generation (RAG) frameworks with LLMs and articulate their advantages.\r\nLead engineering efforts in ML/GenAI model workflows and deployment frameworks.\r\nDevelop AI pipelines for data ingestion, preprocessing, and retrieval to meet technical and business requirements.\r\nImplement CI/CD pipelines for machine learning models, automating testing and deployment.\r\nEstablish monitoring and logging solutions to track model performance and system health.\r\nApply version control systems for ML models and associated code.\r\nEnsure compliance with healthcare regulations, data protection, and privacy standards.\r\nMaintain clear and comprehensive documentation of MLOps processes and configurations.\r\nRequired Qualifications Bachelor's degree in computer science, artificial intelligence, informatics, or related field.\r\nMinimum of 3 years of relevant machine learning engineering experience.\r\nExperience managing end-to-end ML lifecycle.\r\nProficiency with automation tools such as Terraform.\r\nExpertise in containerization technologies (Docker) and orchestration platforms (Kubernetes).\r\nExperience with CI/CD tools (e.g., GitHub Actions).\r\nStrong programming skills in Python, R, and SQL.\r\nDeep understanding of coding, architecture, and deployment processes.\r\nStrong knowledge of critical performance metrics for ML systems.\r\nExtensive experience in predictive modeling, LLMs, and NLP.\r\nFamiliarity with healthcare regulations, standards, and EHR systems integration.\r\nPreferred Qualifications Master's degree in computer science, engineering, or related field.\r\nExperience with cloud platforms (AWS, Azure, GCP).\r\nBackground in healthcare data and machine learning use cases.\r\nTechnical writing and documentation experience for AI/ML models and processes.\r\nCertifications (if any) None required; certifications in cloud platforms, DevOps, or machine learning are a plus.\r\nJ-18808-Ljbffr","company":"Compunnel","rawCompany":"compunnel","city":"Los Angeles","state":"CA","isRemote":false,"isActive":true,"createdAt":"2026-06-25T01:12:01.698Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"622110","title":"General Medical and Surgical Hospitals","slug":"general-medical-and-surgical-hospitals"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Operations Engineer","description":"The Machine Learning Operations (MLOps) Engineer is responsible for the full lifecycle management of machine learning models, including design, build, deployment, and maintenance. This role plays an integral part in implementing artificial intelligence solutions across Keck Medicine of USC, partnering with data scientists, engineers, and clinical operations teams to deliver scalable, reliable, and compliant AI solutions. The MLOps Engineer ensures seamless integration, automation, and monitoring of models within production environments, leveraging DevOps expertise to advance patient care, operational excellence, and clinical research.\r\nKey Responsibilities Design, build, deploy, and maintain machine learning models across production environments.\r\nPartner with data scientists, engineers, and clinical operations to implement AI solutions.\r\nDevelop and continuously improve MLOps pipelines for monitoring, versioning, and deployment.\r\nImplement best practices for testing, debugging, and performance monitoring of AI systems.\r\nEnsure seamless integration, automation, and scaling of AI solutions within existing infrastructure.\r\nSupport predictive modeling, large language models (LLMs), and natural language processing (NLP) initiatives.\r\nApply Retrieval-Augmented Generation (RAG) frameworks with LLMs and articulate their advantages.\r\nLead engineering efforts in ML/GenAI model workflows and deployment frameworks.\r\nDevelop AI pipelines for data ingestion, preprocessing, and retrieval to meet technical and business requirements.\r\nImplement CI/CD pipelines for machine learning models, automating testing and deployment.\r\nEstablish monitoring and logging solutions to track model performance and system health.\r\nApply version control systems for ML models and associated code.\r\nEnsure compliance with healthcare regulations, data protection, and privacy standards.\r\nMaintain clear and comprehensive documentation of MLOps processes and configurations.\r\nRequired Qualifications Bachelor's degree in computer science, artificial intelligence, informatics, or related field.\r\nMinimum of 3 years of relevant machine learning engineering experience.\r\nExperience managing end-to-end ML lifecycle.\r\nProficiency with automation tools such as Terraform.\r\nExpertise in containerization technologies (Docker) and orchestration platforms (Kubernetes).\r\nExperience with CI/CD tools (e.g., GitHub Actions).\r\nStrong programming skills in Python, R, and SQL.\r\nDeep understanding of coding, architecture, and deployment processes.\r\nStrong knowledge of critical performance metrics for ML systems.\r\nExtensive experience in predictive modeling, LLMs, and NLP.\r\nFamiliarity with healthcare regulations, standards, and EHR systems integration.\r\nPreferred Qualifications Master's degree in computer science, engineering, or related field.\r\nExperience with cloud platforms (AWS, Azure, GCP).\r\nBackground in healthcare data and machine learning use cases.\r\nTechnical writing and documentation experience for AI/ML models and processes.\r\nCertifications (if any) None required; certifications in cloud platforms, DevOps, or machine learning are a plus.\r\nJ-18808-Ljbffr","datePosted":"2026-06-25T01:12:01.698Z","dateModified":"2026-06-25T01:12:01.698Z","hiringOrganization":{"@type":"Organization","name":"Compunnel","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Los Angeles","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"e4a58375b2a3ef3f3fdb2abe"},"url":"https://jobsearcher.com/jobs/e4a58375b2a3ef3f3fdb2abe"}}