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Machine Learning Operations Jobs in Illinois (NOW HIRING)

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Push the envelope on our operational efficiency by continually refining and advancing our ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Push the envelope on our operational efficiency by continually refining and advancing our ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Push the envelope on our operational efficiency by continually refining and advancing our ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Push the envelope on our operational efficiency by continually refining and advancing our ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Push the envelope on our operational efficiency by continually refining and advancing our ...

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior ... Push the envelope on our operational efficiency by continually refining and advancing our ...

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Machine Learning Operations information

What are machine learning operations?

Machine Learning Operations (MLOps) is a set of practices that combines machine learning, software engineering, and DevOps to deploy, monitor, and maintain machine learning models in production environments. It involves tasks such as model versioning, automation, testing, and ensuring scalability and reliability using tools like CI/CD pipelines and cloud platforms.

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.

Is machine learning operations a high paying job?

Machine Learning Operations (MLOps) roles typically offer high salaries due to the specialized skills required, such as expertise in cloud platforms, automation, and data engineering. Compensation varies based on experience, location, and company size, but generally ranks above average compared to other tech roles.
What cities in Illinois are hiring for Machine Learning Operations jobs? Cities in Illinois with the most Machine Learning Operations job openings:
Infographic showing various Machine Learning Operations job openings in Illinois as of August 2026, with employment types broken down into 87% Full Time, 10% Part Time, 1% Temporary, and 2% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution.

Machine Learning Operations Analyst

Initio Capital

Chicago, IL โ€ข Remote

$101K - $120K/yr

Full-time

Posted 11 days ago


Job description

ABOUT INITIO CAPITAL

Initio Capital is hiring for this role and related opportunities across consulting, finance, product, software, AI, operations, market research, and growth-focused workstreams.

THE ROLE

As a Machine Learning Operations Analyst, you will help identify promising markets, companies, products, operators, and investment or growth opportunities. You will turn ambiguous information into clear research, structured analysis, prioritized target lists, and practical recommendations.

This is a remote, flexible role for candidates who are analytical, commercially curious, and comfortable moving quickly across business, finance, technology, and strategy topics.

WHAT YOU MAY WORK ON
  • Research companies, markets, business models, and investment themes.
  • Build target lists, market maps, competitive scans, and opportunity pipelines.
  • Analyze data, documents, websites, interviews, and public information to form concise recommendations.
  • Support strategy, sourcing, diligence, product, growth, finance, and operations projects.
WHO THIS IS FOR

This is a strong fit for candidates interested in consulting, finance, investment research, product strategy, software, AI/data, business operations, corporate development, private markets, or entrepreneurship.

COMPENSATION

Compensation varies by project and experience. Many roles are flexible, remote, and project-based.