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Mlops Machine Learning Engineer Jobs in Northbrook, IL

Co-Sourcing Partners

GCP AI/ML Engineer

Chicago, IL · On-site

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or related field. * 4+ years of experience in machine learning engineering or MLOps. * Hands-on experience with Google ...

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL

$126K - $166K/yr

Sr Data Engineer - GE07BE We're determined to make a difference and are proud to be an insurance ... The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ...

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and offsites * Equipment and learning budget to help you do your best work and keep up with the ...

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off‑sites * Equipment and learning budget to help you do your best work and keep up with ...

ADDSOURCE

Data Science/MLOps Engineer

Chicago, IL · On-site

$118K - $141K/yr

Role : Data Science/MLOps Engineer Experience: - Min 8+ Years Location: - Chicago, IL We are ... Build, train, evaluate, and deploy machine learning and data science models for production use.

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off-sites * Equipment and learning budget to help you do your best work and keep up with ...

Coinflow

Machine Learning Lead

Chicago, IL · On-site

$225K - $275K/yr

Partner with Engineering, Product, and Operations to embed fraud intelligence directly into payment ... Experience developing, managing, and scaling MLOps pipelines and monitoring systems (retraining ...

Unchain Data

Machine Learning Lead

Chicago, IL · On-site

$225 - $275/hr

Partner with Engineering, Product, and Operations to embed fraud intelligence directly into payment ... Experience developing, managing, and scaling MLOps pipelines and monitoring systems (retraining ...

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All JobsMlops Machine Learning Engineer JobsMlops Machine Learning Engineer Jobs in Northbrook, IL

Mlops Machine Learning Engineer information

See Northbrook, IL salary details

$32K

$130.7K

$196.4K

How much do mlops machine learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for mlops machine learning engineer in Northbrook, IL is $130,699.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,000.00 and $157,300.00 per year, depending on experience, location, and employer.

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Northbrook, IL?

For Mlops Machine Learning Engineer jobs in Northbrook, IL, the most frequently searched job titles are:

What job categories do people searching Mlops Machine Learning Engineer jobs in Northbrook, IL look for?

The top searched job categories for Mlops Machine Learning Engineer jobs in Northbrook, IL are:

What cities near Northbrook, IL are hiring for Mlops Machine Learning Engineer jobs?

Cities near Northbrook, IL with the most Mlops Machine Learning Engineer job openings:

Mlops Machine Learning Engineer jobs near you
Infographic showing various Mlops Machine Learning Engineer job openings in Northbrook, IL as of June 2026, with employment types broken down into 1% Internship, 2% As Needed, 92% Full Time, 3% Part Time, and 2% Contract. Highlights an 77% Physical, 6% Hybrid, and 17% Remote job distribution, with an average salary of $130,699 per year, or $62.8 per hour.

Senior Machine Learning Engineer

Uber Technologies, Inc.

Chicago, IL • On-site, Remote

Full-time

Retirement

Posted 22 days ago

Uber rating

6.7

Company rating: 6.7 out of 10

Based on 116 frontline employees who took The Breakroom Quiz

4th of 9 rated taxi private hire

Job description

About the Role

Uber Freight Marketplace is building the next generation of logistics technology by leveraging Uber's proven marketplace playbook to freight. As part of a small, high-impact team, you'll help bring expertise from Uber's mobility and delivery marketplaces into a rapidly evolving industry, developing pricing, matching, recommendation, and optimization systems that will disrupt the freight industry ($1T TAM). Uber Freight is at a very early stage, with just 0.4% of the pie now, and it's a rare opportunity to solve challenging marketplace problems with AI/ML and marketplace optimization while shaping how the freight industry transforms.

We are looking for a highly motivated Machine Learning Engineer to join Uber's Marketplace team to modernize the Uber Freight marketplace team. It is a fascinating area with challenges in predictive modeling, causal inference, constrained optimization, reinforcement learning, marketplace design, etc. The business is about to elevate and this role has a huge growing opportunity.

What You'll Do

This role requires end to end ownership for the ML models in UF marketplace (cost prediction, booking probability, demand elasticity, etc.). While your job is mostly about model development, you will work with backend engineers together to put them in production and make sure they work as expected.

Basic Qualifications
 

  • 4+ years of experience developing ML models to solve business problem.
  • Bachelor's degree in Computer Science, Computer Engineering, or related fields.
  • Familiar with modern AI/ML frameworks (e.g., PyTorch).

 Preferred Qualifications

  • Product experience will be a big plus for this role. Adaptive development of ML models to the business context is critical. 
  • Previous experience with state-of-the-art marketplace technology is preferred.
  • Experience with causal inference and constrained optimization

Ready to Ride?


This isn't the kind of place where you follow a playbook - it's where you help write one. If you're driven by impact, energized by challenge, and ready to shape how the world moves - we'd love to hear from you.


You may be eligible for bonuses, equity, and other compensation, as well as a range of benefits. Explore our benefits.


Offices remain key to collaboration and Uber's culture. Unless approved for full remote work, employees must spend at least 50% of their time in-office. Some roles, like those at greenlight hubs, require full-time in-office presence. Ask your Recruiter for details about this role's requirements.


Uber is proud to be an Equal Opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you have a disability or special need that requires accommodation, please let us know by completing this form.

For Chicago, IL-based roles: The base salary range for this role is USD $182,000 per year - USD $202,000 per year.


For New York City, NY-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.


For San Francisco, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.


For Seattle, WA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.


For Sunnyvale, CA-based roles: The base salary range for this role is USD $202,000 per year - USD $224,000 per year.


For all US locations, you will be eligible to participate in Uber's bonus program, and may be offered an equity award & other types of comp. All full-time employees are eligible to participate in a 401(k) plan. You will also be eligible for various benefits.

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