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Engineer II, Machine Learning Ops CBM Lab

Shirley Ryan AbilityLab · Chicago, IL · $72,600–$120,600 a year · Full time

Posted May 20, 2026 · We last checked this listing on Oct 6, 2026

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Likely interview questions for this role

Written from this job description, not a generic list. Each one notes what the interviewer is really checking.

About your past

Tell me about a time you made a model pipeline faster or cheaper to run.

What they are checking: Whether they improve efficiency of deployed models, which the posting names as part of the role.

You work under general supervision. Tell me about a project where you had to figure out the plan yourself.

What they are checking: Whether they can work with some independence at an Engineer II level without needing step-by-step direction.

What would you do

A researcher wants to deploy a new model version today, but the tests aren't done. What do you do?

What they are checking: Whether they can hold quality standards with a researcher while still helping them move quickly.

How would you explain to a clinician why a model's prediction changed between two versions?

What they are checking: Whether they can communicate model behavior clearly to non-engineers who depend on it.

A model works on the lab's data but performs poorly on data from a new clinical site. How do you investigate?

What they are checking: Whether they know how differences in data collection and populations can break models and how to diagnose it.

About the work

Walk me through how you'd take a model a researcher trained in a notebook and get it running reliably in production.

What they are checking: Whether they know the steps of operationalizing models, like packaging, versioning, testing and deployment.

How would you monitor a deployed model to know when its performance is slipping?

What they are checking: Whether they plan for data drift and performance tracking instead of treating deployment as the finish line.

What tools have you used for ML lifecycle management, like experiment tracking or model registries?

What they are checking: Whether they have hands-on experience with the MLOps tools that keep models reproducible and traceable.

The models here may use patient data from a rehab hospital. How does that change how you build pipelines?

What they are checking: Whether they think about privacy, HIPAA and access controls as part of the engineering work.

How do you make a model's results reproducible months after it was trained?

What they are checking: Whether they version data, code and environment so research results can be traced and repeated.

Practice this interview out loud.

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The full job description

As published by Shirley Ryan AbilityLab.

Shirley Ryan AbilityLab is the global leader in physical medicine and rehabilitation for adults and children with the most severe, complex conditions. By joining our team, you’ll be part of our life-changing mission and vision. You’ll contribute to an innovative, multifaceted culture that is second to none — one that embraces collaboration, excellence, discovery and compassion. You’ll play a role in something that’s never been done before as we integrate science and clinical care to help patients achieve better, faster outcomes — as we Advance Human Ability, together. Job Description Summary The Machine Learning Ops Engineer II works under general supervision and plays an active role in the design, development, and/or operationalization of machine learning models. This position involves responsibility in planning and managing artificial intelligence (AI) and machine learning (ML) lifecycle processes and contributing to the efficiency and effectiveness of deployed models. The Machine Learning Ops Engineer II will consistently demonstrate support of the Shirley Ryan AbilityLab statement of Vision, Mission and Core Values by striving for excellence, contributing to the team efforts and showing respect and compassion for patients and their families, fellow employees, and all others with whom there is contact at or in the interest of the institute. The Machine Learning Ops Engineer II will demonstrate Shirley Ryan AbilityLab Core Attributes: Communication, Accountability, Flexibility/Adaptability, Judgment/Problem Solving, Customer Service and Core Values (Hope, Compassion, Discovery, Collaboration, and Commitment to Excellence) while fulfilling job duties. Job Description The Machine Learning Engineer II will: • Actively participates in deploying, monitoring, and scaling machine learning models in production and big data research. • Evaluate data sets to determine suitability for applying machine learning models and techniques. • Guide and assist with the collection and curation of clinical datasets. • Assist in the implementation and evaluation of machine learning algorithms. • Develop and maintain continuous integration and continuous deployment pipelines for automated training and deployment of machine learning models. • Manage machine learning infrastructure and optimizes resource utilization. • Implement monitoring solutions for model performance and health. • Lead small projects or initiatives related to machine learning operations. • Work collaboratively with data scientists to optimize model performance. • Advocate for best practices in machine learning operations within the team. • Participate in maintaining a safe work environment through adherence to policies and procedures relative to safety, fire prevention, hazard communications, security, equipment use and maintenance, infection control and vehicle safety. • Perform all other duties that may be assigned in the best interest of the Shirley Ryan AbilityLab. Reporting Relationships: • Reports directly to a designed engineering manager. Knowledge, Skills & Abilities Required • A professional level of knowledge in computer science, engineering or a related field, typically acquired through a Bachelor’s Degree. • Minimum of 3 years of related experience working on problems of moderate scope where analysis of situations or data requires a review of a variety of factors. • Continues to develop professional expertise, applying institute policies and procedures to resolve a variety of issues. • Proficient in using version control systems, especially Git. • Able to manage branches, handle merge conflicts, and understand the importance of commit history and reverting changes. • Strong skills in Python and experience with machine learning frameworks. • Working proficiency with Linux and Windows operating systems. • Familiarity with tools for deploying machine learning pipelines (eg Docker, Kubenates). • Familiarity with cloud based production pipelines offered by leading manufacturers (eg Microsoft Azure, Amazon Web Services, Google Cloud, etc). • Ability to work independently on assigned tasks and lead small projects. Excellent problem-solving skills and the ability to troubleshoot complex issues. • Good communication skills in both written and verbal forms. Able to work with research subjects and clinicians in a clinical setting. • Able to take direction and complete defined tasks in addition to anticipating and executing follow-up actions. • Able to perform assignments by receiving general instructions on routine work, and detailed instructions on new projects or assignments. • Able to exercise judgment within defined procedures and practices to determine appropriate action. • Able to build stable working relationships with multidisciplinary team. Working Conditions • Normal office environment with little or no exposure to dust or extreme temperature. The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not intended to be construed as an exhaustive list of all responsibilities, duties and skills required of personnel so classified. Pay and Benefits*: Pay Range: $72,600.00 - $120,600.00 Benefits: Shirley Ryan AbilityLab offers a comprehensive benefits program that is competitive with our industry peers in our geographic locations: https://www.sralab.org/benefits *Benefits and benefits’ eligibility can vary by position. Actual compensation will be determined by equity and qualifications of the role. Equal Employment Opportunity Employer Shirley Ryan AbilityLab is an Equal Employment Opportunity Employer. All applicants will be afforded equal employment opportunity without discrimination because of race, color, religion, sex, marital status, national origin or ancestry, citizenship status, age, disability, sexual orientation, gender identity, genetic information, military status, order of protection status, unfavorable discharge from military service, or any other characteristics protected by law. EEO is the Law | EEO is the Law - Know Your Rights | View our Full Policy Shirley Ryan AbilityLab is an Affirmative Action Employer as required by law.

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