ZipRecruiter

Log In

1

Machine Learning Engineer Python Jobs in Illinois

IMC Inc

Hardware Machine Learning Engineer

Chicago, IL

$200K - $225K/yr

Hardware Machine Learning Engineer Chicago, United States; New York, United States We are deploying ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

Synergistic it

AI & Machine Learning Engineer

Chicago, IL

$118K - $141.80K/yr

... Python/Java developer , data analyst , data engineer , data scientist , and machine learning/AI ... engineer . In other words, SynergisticIT focuses on building candidates across Java / Full Stack ...

Lessen

Machine Learning Engineer II

Chicago, IL · On-site

$100.40K - $137.50K/yr

The Machine Learning Engineer II role is part of the Technology Team, which is responsible for ... Programming Languages: SQL, Python * Understanding of ETL tools and database architecture

IMC Inc

Principal Machine Learning Engineer

Chicago, IL

$200K - $250K/yr

We're looking for a Principal Machine Learning Engineer to help shape the next phase of our ... Deep proficiency in Python, with strong experience in either CUDA or C++ * Hands-on expertise with ...

The Hartford

Senior AI Machine Learning Engineer

Chicago, IL · Hybrid

$126.20K - $166.40K/yr

As a Senior Machine Learning Engineer , you will play a critical role in designing, building, and ... Strong object oriented development experience using Python, Java, C# * Familiarity with big data ...

IMC

Hardware Machine Learning Engineer

Chicago, IL

$127.20K - $167.90K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... Proficiency in Python, C++, or similar languages for tooling, testing, and simulation * Strong ...

next page

Showing results 1-20

People also search for

All JobsMachine Learning Engineer Python JobsMachine Learning Engineer Python Jobs in Illinois

Machine Learning Engineer Python information

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

To thrive as a Machine Learning Engineer Python, you need a solid background in computer science, statistics, and mathematics, along with proficiency in Python programming and machine learning concepts. Familiarity with frameworks such as TensorFlow, PyTorch, Scikit-learn, and experience with cloud platforms or MLOps tools are highly valued, as are certifications like Google Professional Machine Learning Engineer. Strong problem-solving abilities, communication skills, and a collaborative mindset help set you apart in this field. These skills enable engineers to design, implement, and deploy effective machine learning solutions that address real-world challenges in dynamic, team-oriented environments.

What are some common challenges faced by Machine Learning Engineers working with Python, and how can they be addressed?

Machine Learning Engineers using Python often encounter challenges such as managing large datasets, ensuring efficient model deployment, and maintaining reproducibility of experiments. Handling data pipelines and model versioning can be complex, especially as projects scale. To address these issues, engineers typically use tools like Pandas and Dask for data handling, Docker for containerization, and MLflow or DVC for tracking experiments and models. Collaborating closely with data engineers, software developers, and product teams is also essential to streamline workflows and ensure models are production-ready.

What is a Machine Learning Engineer Python?

A Machine Learning Engineer Python is a professional who uses the Python programming language to design, build, and deploy machine learning models and systems. They work with large datasets, develop algorithms, and use Python libraries such as TensorFlow, scikit-learn, and PyTorch to solve complex problems. Their responsibilities also include preprocessing data, training models, evaluating performance, and integrating solutions into production environments. Machine Learning Engineers often collaborate with data scientists, software engineers, and business stakeholders to create scalable and efficient machine learning applications.

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

AspectMachine Learning Engineer PythonData Scientist
Required CredentialsBachelor's/Master's in CS, Data Science, or related; Python skills; ML certificationsBachelor's/Master's in Statistics, CS, or related; Python/R skills; Data analysis certifications
Work EnvironmentDevelops scalable ML models, deploys algorithms, collaborates with engineering teamsAnalyzes data, builds models, interprets results, communicates insights
Employer & Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research institutions

While both roles require Python proficiency and data skills, Machine Learning Engineers focus on building and deploying scalable ML models, whereas Data Scientists analyze data and generate insights. The roles often overlap but differ in their primary focus and responsibilities.

What are popular job titles related to Machine Learning Engineer Python jobs in Illinois? For Machine Learning Engineer Python jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Python jobs in Illinois look for? The top searched job categories for Machine Learning Engineer Python jobs in Illinois are:
What cities in Illinois are hiring for Machine Learning Engineer Python jobs? Cities in Illinois with the most Machine Learning Engineer Python job openings:
Machine Learning Engineer Python jobs near you
Infographic showing various Machine Learning Engineer Python job openings in Illinois as of May 2026, with employment types broken down into 41% Full Time, 57% Part Time, and 2% Contract. Highlights an 94% Physical, 1% Hybrid, and 5% Remote job distribution.

Machine Learning Engineer / Scientist

Until

Mundelein, IL • On-site

Full-time

Posted 10 days ago

Job description

Until is a moonshot company building a “pause button” for biology. Our near-term focus is organ-scale reversible cryopreservation: preserving donated organs at subzero temperatures without ice formation, then rewarming them uniformly for transplant. By solving this grand challenge, we’re laying the foundation for whole-body reversible cryopreservation, giving patients a bridge to future cures.

To achieve our goal, we are assembling an interdisciplinary team to develop perfusion systems, cryoprotectant formulations, and vitrification and rewarming hardware. We are also building out our medical hibernation team to tackle the challenges of whole-body cryopreservation, beginning with rodent models.

We envision a future where no transplantable organ is lost to logistics, and no terminal diagnosis is final because patients can safely wait for future medicine to arrive.

About the Role
As a Machine Learning Engineer / Scientist at Until, you will be an early member of the computational team defining how experimental data becomes insight and drives the next round of scientific discovery. You’ll build high-leverage ML systems that help develop new cryoprotectant formulations, engineer biologically-inspired antifreeze proteins, and understand the physics of vitrification and rewarming. You will own projects end-to-end including shaping data collection and designing data pipelines, training and evaluating models, and deploying tooling that scientists use daily. 
About You
  • Degree in Computer Science or a related field (Applied Mathematics, Statistics, Data Science, Computational Biology).
  • Excellent foundations in the mathematics that underlies machine learning, including linear algebra, probability, statistics, and calculus. 
  • Strong experience in modern machine learning approaches, such as representation learning, generative modeling, active learning, and bayesian optimization.
  • Track record of developing ML approaches for scientific discovery, as evidenced by a strong publication record, substantial open source contributions, or deployment of a machine learning system in an industry role.
  • Demonstrated ability to write modular, maintainable, and performant code in Python.
  • Fluency with the Python data science and ML stack, including PyTorch, NumPy, SciPy, Pandas/Polars, Matplotlib/Plotly.
  • Proficient with developer tooling, including Linux command line, Git, and shell scripting.
  • Ability to think from first principles and tackle complex, cross-disciplinary problems with other scientists and engineers.
Preferred Qualifications
  • 3+ years of relevant professional or research experience, or a PhD in a computational field.
  • Strong understanding of computer science fundamentals, including algorithms, operating systems, and concurrency. 
  • Experience with cloud infrastructure (AWS, GCP) and SQL databases.
Benefits
  • Opportunity for outsized impact creating the future as an early team member
  • Generous medical, dental and vision insurance coverage
  • Flexible time off and paid holidays
  • Competitive compensation package, including salary and equity
  • 401(k) retirement savings plan
  • FSA and commuter benefits
  • Subsidized lunch daily
While this represents our expected range based on market data, final compensation will be determined based on your specific qualifications and may be outside this range. Please keep in mind that the equity portion of the offer is not included in this estimate.
As an equal opportunity employer, Until is committed to providing employment opportunities to all individuals. All applicants for positions at Until will be treated without regard to race, color, ethnicity, religion, sex, gender, gender identity and expression, sexual orientation, national origin, disability, age, marital status, veteran status, pregnancy, or any other basis prohibited by applicable law.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.