Machine Learning Engineer
Keck Medicine of USC - Los Angeles, CA
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***** 3 or more years relevant Machine Learning Engineer ExperienceBachelor's Degree computer science, artificial intelligence, informatics or closely related field Masters preferred Healthcare ***** Understanding of healthcare regulations and standards, and familiarity with Electronic Health Records (EHR) systems, including integrating machine learning models with these systems.Job ***** Production Deployment and Model ***** Proven experience in deploying and maintaining production-grade machine learning models, with real-time inference, scalability, and reliability.Scalable ML ***** Proficiency in developing end-to-end scalable ML infrastructures using on-premise cloud platforms such as Amazon Web Services (AWS), Google Cloud Platform (GCP), or Azure.Engineering ***** Ability to lead engineering efforts in creating and implementing methods and workflows for ML/GenAI model engineering, LLM advancements, and optimizing deployment frameworks while aligning with business strategic directions.AI Pipeline ***** Experience in developing AI pipelines for various data processing needs, including data ingestion, preprocessing, and search and retrieval, ensuring solutions meet all technical and business requirements.***** Demonstrated ability to collaborate with data scientists, data engineers, analytics teams, and DevOps teams to design and implement robust deployment pipelines for continuous improvement of machine learning models.Continuous Integration/Continuous Deployment (CI/CD) ***** Expertise in implementing and optimizing CI/CD pipelines for machine learning models, automating testing and deployment processes.Monitoring and ***** Competence in setting up monitoring and logging solutions to track model performance, system health, and anomalies, allowing for timely intervention and proactive maintenance.Version ***** Experience implementing version control systems for machine learning models and associated code to track changes and facilitate collaboration.Security and ***** Knowledge of ensuring machine learning systems meet security and compliance standards, including data protection and privacy regulations.***** Skill in maintaining clear and comprehensive documentation of ML Ops processes and configurations.**Proficiency in Containerization ** Experience with Docker, Kubernetes, or similar tools. Certification(s) in Machine Learning a plus
Created: 2025-02-19