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Job Summary Fully Remote Key Bank Tower Full time R181173
Job Description:
Machine Learning Operations Engineers enable development end-to-end data science applications that apply predictive, prescriptive, and cognitive analytic methods to system-wide clinical and operational strategic initiatives and analytics products that serve both internal and external customers. Using industry leading data science and artificial intelligence (AI) practices to deliver on our mission to accelerate the transition from volume to value-based systems of care, improve outcomes, and make costs more affordable. Machine Learning Ops Engineers are responsible for working closely with our data scientists, data architects / engineers, and software engineers to build and deploy machine learning solutions that solve real-world problems in the healthcare industry. We are committed to offering flexible work options where approved and stated in the job posting. However, we are currently not considering candidates who reside or plan to reside in the following states: California, Connecticut, Hawaii, Illinois, Maine, Massachusetts, Minnesota, New York, Pennsylvania, Rhode Island, Virginia, Vermont, Washington. Please note that a video interview through Microsoft Teams will be required as well as potential onsite interviews and meetings Job Essentials Machine Learning Operational Engineers develop machine learning engineering frameworks to enable governance, testing, and automation using best practices in continuous integration and continuous delivery. They build and deploy machine learning platforms leveraging model registries, feature stores, model monitoring, etc. and operationalize and optimize data science models to ensure reliability, scalability, and maximum performance. They automate the retraining, maintenance, and monitoring of models in production, ensure data science models follow best practices in Responsible AI and stay up to date with the latest machine learning technologies and techniques. The Senior level Machine Learning Operations Engineer works on projects that are highly complex in nature, needing subject matter expertise and experience to perform successfully. This position may serve as a subject matter expert and resource for others and will deploy and maintain innovative data science tools and methods that result in products or strategic insights with significant return on investment while meeting project requirements and timelines. Develops efficient and scalable machine learning systems that enable integration of data science applications into healthcare operations, strategy, value improvement, care advancement, patient safety and satisfaction. Partners with data scientists, application developers, data architects, and system engineers to recommend and develop ML systems and pipelines and quickly learns and appropriately applies cutting edge advanced analytic methodologies and tools in creative and novel ways. The Senior level also directs and pilots initiatives from inception to workflow integration, including engaging stake holders, analytics, data science, data architecture / engineering, and software engineering teams. Skills AI/ML modeling techniques MLOps platforms Programming languages DevOps practices Data manipulation
Cloud Computing Responsible AI Processing and Monitoring Minimum Qualifications:
Experience leading the development of MLOps machine learning platforms leveraging model registries, feature stores, model monitoring, etc. Successful experience leading the development, implementation, and administration of machine learning systems and pipelines within operational workflows from end-to-end. Computer Occupations, All Other
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