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Machine Learning Operations Jobs in Illinois (NOW HIRING)

The Hartford

AI Machine Learning Engineer

Chicago, IL · Hybrid

$100K - $151K/yr

The Hartford is seeking AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading AI and ...

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL · Hybrid

$126K - $166K/yr

Within Customer Operations Data Science, we build modern AI products that optimize customer ... As a Senior Machine Learning Engineer , you will play a critical role in designing, building, and ...

The Hartford

Sr AI Machine Learning Engineer

Chicago, IL · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations (MLOps) services for the Global Specialty Applied AI team. The Hartford is developing industryleading ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

... , and Delivery Platforms to understand requirements and ensure alignment of machine learning ... engineering solutions with overall business objectives and priorities. * Leverage cutting-edge big ...

Paylocity

Senior Machine Learning Engineer

Schaumburg, IL · On-site

$120K - $159K/yr

... , and Delivery Platforms to understand requirements and ensure alignment of machine learning engineering solutions with overall business objectives and priorities. • Leverage cutting-edge big data ...

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All JobsMachine Learning Operations JobsMachine Learning Operations Jobs in Illinois

Machine Learning Operations information

Is ML a high paying job?

Machine Learning Operations (MLOps) roles are generally well-paid due to the specialized skills required, such as expertise in cloud platforms, programming, and data management. Salaries tend to be higher than average tech roles and can increase with experience, certifications, and knowledge of tools like TensorFlow or Kubernetes.

What is the difference between Machine Learning Operations vs Data Scientist?

AspectMachine Learning OperationsData Scientist
Primary FocusDeploying, maintaining, and scaling ML models in productionAnalyzing data to develop insights and build models
Required SkillsML deployment, cloud platforms, automation, scriptingStatistical analysis, data visualization, programming (Python/R)
Work EnvironmentOperations teams, cloud infrastructure, production systemsResearch environments, data analysis teams, R&D
Common CertificationsCloud certifications, MLOps tools certificationsData science certifications, statistical courses

Machine Learning Operations and Data Scientists often collaborate, but MLOps focuses on deploying and maintaining models in production, while Data Scientists focus on analyzing data and developing models. Both roles require technical skills, but their day-to-day tasks and environments differ.

What engineer makes $500,000 a year?

Senior machine learning operations engineers with extensive experience, advanced skills in automation, cloud platforms, and deployment pipelines can earn salaries approaching or exceeding $500,000 annually, especially in high-cost-of-living areas or large tech companies. Such roles often require expertise in tools like Kubernetes, Docker, and cloud services, along with strong problem-solving and leadership abilities.

What is a $900000 AI job?

A $900,000 AI job typically refers to high-level roles in artificial intelligence, such as senior machine learning engineers, AI research directors, or chief AI officers, often requiring advanced skills in machine learning, deep learning, and data science. These positions usually involve leadership responsibilities, extensive experience, and may include stock options or bonuses that contribute to the total compensation. Such roles are rare and highly competitive, often found in large tech companies or innovative startups.

Will MLE be replaced by AI?

Machine Learning Engineers (MLEs) design, develop, and maintain AI systems, and while AI automation tools can handle certain tasks, MLEs are essential for creating, tuning, and overseeing complex models. AI may automate some routine aspects, but MLEs' expertise in data engineering, model optimization, and deployment remains critical for effective AI solutions.
What cities in Illinois are hiring for Machine Learning Operations jobs? Cities in Illinois with the most Machine Learning Operations job openings:
Machine Learning Operations jobs near you
Infographic showing various Machine Learning Operations job openings in Illinois as of July 2026, with employment types broken down into 1% As Needed, 79% Full Time, 18% Part Time, 1% Temporary, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution.
Engineer II, Machine Learning Ops CBM Lab

Engineer II, Machine Learning Ops CBM Lab

Shirley Ryan AbilityLab

Chicago, IL • On-site

Full-time

Re-posted 19 days ago

Shirley Ryan AbilityLab rating

6.4

Company rating: 6.4 out of 10

Based on 12 frontline employees who took The Breakroom Quiz

Job description

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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