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Machine Learning Engineer Jobs in Gurnee, IL (NOW HIRING)

Deloitte

Data Scientist

Arlington Heights, IL · On-site

... or Machine Learning role. * 5+ Years of Experience Proficiency in programming languages such as Python or R. * 5+ Years of Experience with Strong knowledge of machine learning techniques and ...

Deloitte

Data Scientist

Arlington Heights, IL · On-site

... or Machine Learning role. * 5+ Years of Experience Proficiency in programming languages such as Python or R. * 5+ Years of Experience with Strong knowledge of machine learning techniques and ...

DataAnnotation

DevOps Engineer

Kenosha, WI · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Spruce Infotech

AI Data Solutions Architect

Lincolnshire, IL · On-site

$67 - $86.25/hr

... machine learning initiatives across the organization. The ideal candidate will bring a strong blend of data architecture, cloud and data engineering, and AI enablement experience, ensuring that data ...

DataAnnotation

Software Engineer

Kenosha, WI · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

Epic

Entry-Level Software Developer

Racine, WI · On-site

... Developer to write software that impacts the lives of millions of patients. The role involves ... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ...

Epic

Entry-Level Software Developer

Kenosha, WI · On-site

... Developer to write software that impacts the lives of millions of patients. The role involves ... and machine learning tools to drive innovation in healthcare. • Invent better ways to reduce ...

UL Solutions

Associate Data Scientist

Northbrook, IL · On-site

$60K - $60K/yr

This is a collaborative, applied role working at the intersection of operations, principal engineering, and global technology and other partners. * Develop and apply machine learning and AI methods ...

DataAnnotation

Frontend Engineer

Kenosha, WI · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

DataAnnotation

Mobile Software Engineer

Kenosha, WI · Remote

$40 - $75/hr

As a member of DataAnnotation's coding team, you'll be part of a growing community of over 100,000 professionals -- including front-end, back-end, full-stack, machine learning, and other engineers ...

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All JobsMachine Learning Engineer JobsMachine Learning Engineer Jobs in Gurnee, IL

Machine Learning Engineer information

See Gurnee, IL salary details

$30.2K

$123.6K

$185.7K

How much do machine learning engineer jobs pay per year?

As of Jun 9, 2026, the average yearly pay for machine learning engineer in Gurnee, IL is $123,595.00, according to ZipRecruiter salary data. Most workers in this role earn between $97,400.00 and $148,800.00 per year, depending on experience, location, and employer.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.
More about Machine Learning Engineer jobs
What cities near Gurnee, IL are hiring for Machine Learning Engineer jobs? Cities near Gurnee, IL with the most Machine Learning Engineer job openings:
Machine Learning Engineer jobs near you
Infographic showing various Machine Learning Engineer job openings in Gurnee, IL as of May 2026, with employment types broken down into 1% Internship, 53% Full Time, 44% Part Time, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution, with an average salary of $123,595 per year, or $59.4 per hour.
Senior Manager, Data Science - Anti-Money Laundering Modeling and Advanced Data Insights

Senior Manager, Data Science - Anti-Money Laundering Modeling and Advanced Data Insights

Capital One

Riverwoods, IL

Full-time

Posted 11 days ago

Capital One rating

7.7

Company rating: 7.7 out of 10

Based on 134 frontline employees who took The Breakroom Quiz

72nd of 141 rated banks

Job description

Senior Manager, Data Science - Anti-Money Laundering Modeling and Advanced Data Insights

Data is at the center of everything we do. As a startup, we disrupted the credit card industry by individually personalizing every credit card offer using statistical modeling and the relational database, cutting edge technology in 1988! Fast-forward a few years, and this little innovation and our passion for data has skyrocketed us to a Fortune 200 company and a leader in the world of data-driven decision-making.

As a Data Scientist at Capital One, you'll be part of a team that's leading the next wave of disruption at a whole new scale, using the latest in computing and machine learning technologies and operating across billions of customer records to unlock the big opportunities that help everyday people save money, time and agony in their financial lives.

Team Description

The Anti-Money Laundering (AML) Modeling and Advanced Data Insights team is on a journey to modernize the way Capital One identifies potential money laundering, fraud, terrorist financing, and human trafficking through the use of advanced analytic techniques, statistics, and machine learning models. We develop predictive models, monitoring dashboards, and reporting using tools such as AWS, Snowflake, Python, and Spark. Our team produces the model outputs and data insights to operate our AML program efficiently and effectively. As the model developer for advancing transaction monitoring with machine learning, our team is responsible for end to end development, deployment, and monitoring of production models

Role Description

In this role, you will:

  • Partner with a cross-functional team of data scientists, software engineers, and product managers to deliver a product customers love

  • Leverage a broad stack of technologies - Python, Conda, AWS, H2O, Spark, and more - to reveal the insights hidden within huge volumes of numeric and textual data

  • Build machine learning models through all phases of development, from design through training, evaluation, validation, and implementation

  • Flex your interpersonal skills to translate the complexity of your work into tangible business goals

The Ideal Candidate is:

  • Customer first. You love the process of analyzing and creating, but also share our passion to do the right thing. You know at the end of the day it's about making the right decision for our customers.

  • Innovative. You continually research and evaluate emerging technologies. You stay current on published state-of-the-art methods, technologies, and applications and seek out opportunities to apply them.

  • Creative. You thrive on bringing definition to big, undefined problems. You love asking questions and pushing hard to find answers. You're not afraid to share a new idea.

  • A leader. You challenge conventional thinking and work with stakeholders to identify and improve the status quo. You're passionate about talent development for your own team and beyond.

  • Technical. You're comfortable with open-source languages and are passionate about developing further. You have hands-on experience developing data science solutions using open-source tools and cloud computing platforms.

  • Statistically-minded. You've built models, validated them, and backtested them. You know how to interpret a confusion matrix or a ROC curve. You have experience with clustering, classification, sentiment analysis, time series, and deep learning.

  • A data guru. "Big data" doesn't faze you. You have the skills to retrieve, combine, and analyze data from a variety of sources and structures. You know understanding the data is often the key to great data science.

Basic Qualifications:

  • Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:

    • A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 7 years of experience performing data analytics

    • A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) or an MBA with a quantitative concentration plus 5 years of experience performing data analytics

    • A PhD in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, or a related quantitative field) plus 2 years of experience performing data analytics

  • At least 2 years of experience leveraging open source programming languages for large scale data analysis

  • At least 2 years of experience working with machine learning

  • At least 2 years of experience utilizing relational databases

Preferred Qualifications:

  • PhD in "STEM" field (Science, Technology, Engineering, or Mathematics) plus 4 years of experience in data analytics

  • At least 1 year of experience working with AWS

  • At least 1 year of experience managing people

  • At least 5 years' experience in Python, Scala, or R for large scale data analysis

  • At least 5 years' experience with machine learning, especially in the AML modeling area

Capital One will consider sponsoring a new qualified applicant for employment authorization for this position.

The minimum and maximum full-time annual salaries for this role are listed below, by location. Please note that this salary information is solely for candidates hired to perform work within one of these locations, and refers to the amount Capital One is willing to pay at the time of this posting. Salaries for part-time roles will be prorated based upon the agreed upon number of hours to be regularly worked.

Chicago, IL: $209,000 - $238,500 for Sr Mgr, Data Science


McLean, VA: $229,900 - $262,400 for Sr Mgr, Data Science


Plano, TX: $209,000 - $238,500 for Sr Mgr, Data Science


Richmond, VA: $209,000 - $238,500 for Sr Mgr, Data Science


Riverwoods, IL: $209,000 - $238,500 for Sr Mgr, Data Science







Candidates hired to work in other locations will be subject to the pay range associated with that location, and the actual annualized salary amount offered to any candidate at the time of hire will be reflected solely in the candidate's offer letter.

This role is also eligible to earn performance based incentive compensation, which may include cash bonus(es) and/or long term incentives (LTI). Incentives could be discretionary or non discretionary depending on the plan.

Capital One offers a comprehensive, competitive, and inclusive set of health, financial and other benefits that support your total well-being. Learn more at theCapital One Careers website. Eligibility varies based on full or part-time status, exempt or non-exempt status, and management level.

This role is expected to accept applications for a minimum of 5 business days.No agencies please. Capital One is an equal opportunity employer (EOE, including disability/vet) committed to non-discrimination in compliance with applicable federal, state, and local laws. Capital One promotes a drug-free workplace. Capital One will consider for employment qualified applicants with a criminal history in a manner consistent with the requirements of applicable laws regarding criminal background inquiries, including, to the extent applicable, Article 23-A of the New York Correction Law; San Francisco, California Police Code Article 49, Sections 4901-4920; New York City's Fair Chance Act; Philadelphia's Fair Criminal Records Screening Act; and other applicable federal, state, and local laws and regulations regarding criminal background inquiries.

If you have visited our website in search of information on employment opportunities or to apply for a position, and you require an accommodation, please contact Capital One Recruiting at 1-800-304-9102 or via email at RecruitingAccommodation@capitalone.com. All information you provide will be kept confidential and will be used only to the extent required to provide needed reasonable accommodations.

For technical support or questions about Capital One's recruiting process, please send an email to Careers@capitalone.com

Capital One does not provide, endorse nor guarantee and is not liable for third-party products, services, educational tools or other information available through this site.

Capital One Financial is made up of several different entities. Please note that any position posted in Canada is for Capital One Canada, any position posted in the United Kingdom is for Capital One Europe and any position posted in the Philippines is for Capital One Philippines Service Corp. (COPSSC).

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