Note: The job is a remote job and is open to candidates in USA. Intermountain Health develops healthcare solutions that use data science and artificial intelligence to improve outcomes and make care more affordable. The Machine Learning Operations Engineer builds, deploys, automates, and maintains machine learning platforms and pipelines, partnering with data scientists, architects, and software engineers to support clinical and operational initiatives.
Responsibilities
- 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
- 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
- Interact with others by effectively communicating, both orally and in writing
- Operate computers and other office equipment requiring the ability to move fingers and hands
- See and read computer monitors and documents
- Remain sitting or standing for long periods of time to perform work on a computer, telephone, or other equipment
- May require lifting and transporting objects and office supplies, bending, kneeling and reaching
- 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
Benefits
- Fully Remote
- Flexible work options where approved and stated in the job posting
- 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
Company Overview
Company H1B Sponsorship