Machine Learning Operations Engineer

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.
• 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

Preferred Qualifications:

• 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.

Physical Requirements

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

Location:

Key Bank Tower

Work City:

Salt Lake City

Work State:

Utah

Scheduled Weekly Hours:

40

The hourly range for this position is listed below. Actual hourly rate dependent upon experience. 

$60.67 - $95.52

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.

By applying for a position with Intermountain, I acknowledge that I will comply with all applicable Intermountain policies and expectations. If applying for a remote or hybrid role, this includes remote work expectations related to confidentiality, information security, work schedules, conflicts of interest, and use of company equipment. I further acknowledge that outside employment or activities may not interfere with job responsibilities or create a conflict of interest with Intermountain. Actual or reasonably perceived conflicts may be grounds for disqualification from consideration or, if hired, corrective action up to and including termination of employment.

Intermountain Health is an equal opportunity employer. Qualified applicants will receive consideration for employment without regard to race, color, religion, age, sex, sexual orientation, gender identity, national origin, disability or protected veteran status.

At Intermountain Health, we use the artificial intelligence ("AI") platform, HiredScore to improve your job application experience. HiredScore helps match your skills and experiences to the best jobs for you. While HiredScore assists in reviewing applications, all final decisions are made by Intermountain personnel to ensure fairness. We protect your privacy and follow strict data protection rules. Your information is safe and used only for recruitment. Thank you for considering a career with us and experiencing our AI-enhanced recruitment process.

All positions subject to close without notice.