Machine Learning Operations Engineer

Intermountain Health • Dayton, OH

1d • $61 - $96 • Hybrid

About The Position

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

Requirements

• 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.
• Experience utilizing and creating custom API’s, functions, libraries, and/or packages in multiple programming languages.
• Advanced experience programming and reviewing code using statistical and data software tools like Python, R, Java, Scala, etc.
• Experience with Linux and bash scripting.
• Advanced experience with DevOps best practices (continuous integration and continuous deployment) and tools (such as Docker, Kubernetes, and Git).
• Advanced experience writing and tuning queries to manipulate and combine large or complex data sets, including unstructured data sources.
• Experience using Big Data technologies like Hadoop, Spark, Hive, NoSQL, in-memory data stores, etc., and Cloud technologies such as AWS, Azure, etc.
• Ability to work in a collaborative, remote development environment.
• Skilled in communicating technical insights through data visualization, verbal, written, and interpersonal communication.
• Experience fostering machine learning partnerships across all levels of an organization through effective communication and relationship management

Nice To Haves

• Degree earned in a related field such as data science, computer science, engineering, information systems, or other quantitative and computational discipline.
• Experience using Azure or AWS cloud computing and Databricks.
• Successful experience working in a healthcare or insurance setting.

Responsibilities

• Develop machine learning engineering frameworks to enable governance, testing, and automation using best practices in continuous integration and continuous delivery.
• Build and deploy machine learning platforms leveraging model registries, feature stores, model monitoring, etc.
• Operationalize and optimize data science models to ensure reliability, scalability, and maximum performance.
• 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.
• Works on projects that are highly complex in nature, needing subject matter expertise and experience to perform successfully.
• May serve as a subject matter expert and resource for others.
• 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.
• Quickly learns and appropriately applies cutting edge advanced analytic methodologies and tools in creative and novel ways.
• Directs and pilots initiatives from inception to workflow integration, including engaging stake holders, analytics, data science, data architecture / engineering, and software engineering teams.

Benefits

• We care about your well-being – mind, body, and spirit – which is why we provide our caregivers a generous benefits package that covers a wide range of programs to foster a sustainable culture of wellness that encompasses living healthy, happy, secure, connected, and engaged.
• Learn more about our comprehensive benefits package here.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: Associate degree