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Entrylevel Machine Learning Engineer Jobs in Chicago, IL

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Machine Learning Engineer II

Chicago, IL · On-site

$100K - $137K/yr

The Machine Learning Engineer II role is part of the Technology Team, which is responsible for providing industry-leading machine learning-based tools or processes to the Company, which provide a ...

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 ...

IMC

Hardware Machine Learning Engineer

Chicago, IL

$127K - $167K/yr

... engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production * Track and evaluate emerging research in neural architecture search, machine learning ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

... engineers to implement, verify, and deploy ML inference solutions from proof-of-concept through production * Track and evaluate emerging research in neural architecture search, machine learning ...

Huxley

Senior Machine Learning Engineer

Chicago, IL

$107K - $147K/yr

Our client is looking to bring on a Senior Machine Learning Engineer to help build and scale a nextgeneration voice-centric AI platform used by millions. In this role, you'll own the full ML ...

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All JobsEntrylevel Machine Learning Engineer JobsEntrylevel Machine Learning Engineer Jobs in Chicago, IL

Entrylevel Machine Learning Engineer information

See Chicago, IL salary details

$32.5K

$132.7K

$199.3K

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

As of Jun 9, 2026, the average yearly pay for entrylevel machine learning engineer in Chicago, IL is $132,651.00, according to ZipRecruiter salary data. Most workers in this role earn between $104,600.00 and $159,700.00 per year, depending on experience, location, and employer.

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

AspectEntrylevel Machine Learning EngineerData Scientist
Required CredentialsBachelor's in CS, Math, or related; some knowledge of ML frameworksBachelor's or higher in CS, Statistics, or related; strong analytical skills
Work EnvironmentDevelops ML models, implements algorithms, collaborates with engineering teamsAnalyzes data, builds statistical models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles involve working with data and algorithms, an Entrylevel Machine Learning Engineer primarily focuses on developing and deploying machine learning models within software systems. In contrast, a Data Scientist emphasizes analyzing data, creating statistical models, and deriving insights. Both roles often require similar educational backgrounds, but their day-to-day tasks and industry applications differ.

What cities near Chicago, IL are hiring for Entrylevel Machine Learning Engineer jobs? Cities near Chicago, IL with the most Entrylevel Machine Learning Engineer job openings:
Entrylevel Machine Learning Engineer jobs near you
Applied Machine Learning Engineer

Applied Machine Learning Engineer

Strata Decision Technology

Chicago, IL • On-site

$117K - $150K/yr

Other

Medical, Life, Retirement, PTO

Posted 17 days ago

Job description

How You'll Make an Impact
As an Applied Machine Learning Engineer, you will collaborate with architects, data scientists, agentic AI developers, platform engineers, and the product team to build advanced AI and ML capabilities into our platform. Your work will drive innovation in generative AI and beyond, integrating and customizing a wide range of machine learning techniques to solve complex problems in healthcare. By developing next-generation AI agents, algorithms, and computation engines, you will help Strata strengthen its market leadership, improve operational efficiency, and support healthcare providers in delivering high-quality care while maintaining financial health.

A Day in the Life

  • Read and translate the latest research (e.g., arXiv papers) into production-ready solutions in Python.

  • Prototype and iterate on machine learning models, focusing on areas such as regression, causal inference, optimization, and vector embeddings.

  • Collaborate with cross-functional teams to embed ML and AI capabilities directly into our software platform.

  • Partner with data scientists to design experiments and apply statistical concepts to real-world data.

  • Optimize, test, and scale ML models to support mission-critical healthcare analytics.

Our Technology Stack
Our core platform is used by more than half of the nation's leading healthcare providers, enabling them to leverage financial, operational, and clinical data. Our AI and ML stack includes:

  • Languages & Libraries: Python, PyTorch, NumPy, Pandas, Polars, PyMC

  • Infrastructure: AWS, Snowflake, Docker, GitHub

  • Techniques & Tools:

    • Regression (with and without Bayesian priors)

    • Vector embeddings, similarity, clustering

    • Core statistics and distributions for EDA

    • Optimization methods (multi-armed bandit, mixed integer programming)

    • Causal inference and probabilistic modeling

What We're Looking For
We're seeking a technically curious engineer who thrives on turning theory into practice. The ideal candidate has:

  • Strong experience implementing ML models in Python.

  • Familiarity with regression, embeddings, causal inference, and optimization techniques.

  • Experience applying statistical methods to exploratory data analysis.

  • Comfort working with modern ML libraries and frameworks.

Bonus points if you have worked with:

  • NLP tasks (LLMs, spaCy, neural networks).

  • Recommender systems, latent factors, matrix factorization.

  • Graph algorithms.

  • Claude Code, Docker, and GitHub.ess computation engine.

Estimated Salary Range: $117,000-150,000
Actual salary will be determined based on factors including, but not limited to, skill set and level of experience. This salary range is a good faith estimate of base pay. Strata also provides discretionary variable pay programs based on role. In addition, Strata provides a comprehensive benefits package including retirement benefits, health and welfare benefits, paid time off, parental leave, life and accident insurance, and other voluntary and well-being benefits.

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