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Remote Internship Machine Learning Engineer Jobs in Chicago, IL

Harnham

Senior Machine Learning Engineer

Chicago, IL · Remote

$107K - $147K/yr

Senior Machine Learning Engineer Remote in US $160,000 - $190,000 Base + 10% Bonus THE COMPANY Harnham is partnering with a fintech that has built a leading fraud protection platform enabling ...

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Career Renew

Senior Machine Learning Engineer

Chicago, IL · Remote

$165K - $225K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 165-225K USD yearly plus benefits plus ...

Career Renew

Senior ML Engineer

Chicago, IL · Remote

$180K - $240K/yr

Career Renew is recruiting for one of its clients a Senior Machine Learning Engineer - this is a fully remote role for US/Canada based candidates. Salary range: 180-240K USD plus benefits plus equity.

Varsity Tutors

Machine Learning Tutor

Skokie, IL · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Varsity Tutors

Machine Learning Tutor

Oak Lawn, IL · Remote

$40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

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All JobsRemote Internship Machine Learning Engineer JobsRemote Internship Machine Learning Engineer Jobs in Chicago, IL

Remote Internship Machine Learning Engineer information

See Chicago, IL salary details

$26.3K

$43.9K

$90.7K

How much do remote internship machine learning engineer jobs pay per year?

As of Jun 21, 2026, the average yearly pay for remote internship machine learning engineer in Chicago, IL is $43,867.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,500.00 and $47,400.00 per year, depending on experience, location, and employer.

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

AspectRemote Internship Machine Learning EngineerRemote Data Scientist Intern
Required CredentialsBasic programming, machine learning fundamentals, coursework or certificationsStatistics, data analysis, programming skills, coursework or certifications
Work EnvironmentCollaborative team, remote, project-basedRemote, data analysis projects, team collaboration
Industry UsageTech, AI, software developmentTech, finance, healthcare, research

Both roles are internship positions focused on data and machine learning skills, often requiring similar educational backgrounds. The main difference lies in their focus: Machine Learning Engineers concentrate on developing and deploying ML models, while Data Science Interns focus on analyzing data and deriving insights. Both are common in tech industries and often share similar work environments and prerequisites.

What are popular job titles related to Remote Internship Machine Learning Engineer jobs in Chicago, IL? For Remote Internship Machine Learning Engineer jobs in Chicago, IL, the most frequently searched job titles are:
What job categories do people searching Remote Internship Machine Learning Engineer jobs in Chicago, IL look for? The top searched job categories for Remote Internship Machine Learning Engineer jobs in Chicago, IL are:
What cities near Chicago, IL are hiring for Remote Internship Machine Learning Engineer jobs? Cities near Chicago, IL with the most Remote Internship Machine Learning Engineer job openings:
Remote Internship Machine Learning Engineer jobs near you
Senior Machine Learning Engineer

Senior Machine Learning Engineer

Harnham

Chicago, IL • Remote

$107K - $147K/yr

Other

Posted yesterday

Job description

Senior Machine Learning Engineer

Remote in US

$160,000 – $190,000 Base + 10% Bonus


THE COMPANY

Harnham is partnering with a fintech that has built a leading fraud protection platform enabling merchants to grow confidently by eliminating fraud and delivering frictionless customer experiences. They’re a global company that processes billions of transactions annually, leveraging advanced machine learning to approve more good orders while protecting revenue.

The company combines cutting-edge technology with a deeply collaborative and mission-driven culture. Their Machine Learning team sits at the core of the product, building and maintaining the models and experimentation frameworks that power fraud detection at scale.


RESPONSIBILITIES

  • Own the end-to-end lifecycle of machine learning projects, from experimentation through deployment and production monitoring.
  • Build, maintain, and optimize production-grade machine learning models for fraud detection.
  • Design and implement scalable ML pipelines to enable rapid experimentation and model iteration.
  • Develop advanced feature engineering and statistical methodologies to improve model performance.
  • Collaborate with Product, Engineering, and Risk teams to translate business needs into ML solutions.
  • Contribute to model training, evaluation frameworks, and experimentation infrastructure.
  • Ensure robustness, scalability, and reliability of ML systems in high-volume production environments.
  • Drive best practices in testing, documentation, and model monitoring across the ML team.


SKILLS AND EXPERIENCE

  • 4–6+ years of experience in machine learning within production environments.
  • Strong foundation in machine learning theory, statistical modeling, and evaluation techniques.
  • Experience building and deploying supervised and unsupervised ML models at scale.
  • Proven track record of taking ML projects from research/prototype to production.
  • Proficiency in Python, SQL, and key machine learning libraries.
  • Experience working with distributed data processing tools such as Spark.
  • Strong communication skills, with the ability to explain technical insights to non-technical stakeholders.
  • Detail-oriented mindset with a focus on delivering measurable business impact.


PREFFERED EXPERIENCE

  • Experience in fraud detection, fintech, payments, or e-commerce domains.
  • Advanced degree (Master’s or PhD) in a quantitative field.
  • Passion for writing well-tested, production-quality code.
  • Interest in adversarial machine learning and combating fraud at scale.


BENEFITS

The compensation package includes a competitive base salary, performance-based bonus, and a comprehensive benefits package within a fast-growing, mission-driven organization.


HOW TO APPLY

Please submit your CV via the Apply link on this page to register your interest.


KEY TERMS

Machine Learning | Fraud Detection | Fintech | Payments | E-Commerce | Python | SQL | Spark | Data Science | Statistical Modeling | Feature Engineering | MLOps | Experimentation | Adversarial ML | Production ML Systems

Apply