ZipRecruiter

Log In

1

Machine Learning Research Jobs in Illinois (NOW HIRING)

Gotion, Inc.

Machine Learning Engineer

Manteno, IL · On-site

You will collaborate closely with cross-disciplinary R&D teams to develop and deploy machine ... Design and implement novel machine learning and deep learning models tailored to internal research ...

Vizient

AVP, Machine Learning & Modeling

Chicago, IL

$156K - $290K/yr

Research and Innovation Stay at the forefront of emerging AI and machine learning technologies. Evaluate and integrate new tools, frameworks, and methodologies to enhance model performance and ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

We're looking for researchers and experienced engineers from any background. Trading experience is ... Understanding of machine learning fundamentals - neural network architectures, inference ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$200K - $225K/yr

We're looking for researchers and experienced engineers from any background. Trading experience is ... Understanding of machine learning fundamentals - neural network architectures, inference ...

IMC

Hardware Machine Learning Engineer

Chicago, IL · On-site

$127K - $167K/yr

We are deploying machine learning directly onto custom hardware - and we want you to help drive it ... We're looking for researchers and experienced engineers from any background. Trading experience is ...

Crowe

Machine Learning Intern

Chicago, IL

$27 - $42/hr

Modeling Understanding how to frame business problems as data science problems Navigating the full data science lifecycle: research and exploration, development, deployment, support Using correct ...

Crowe

Machine Learning Intern

Chicago, IL · On-site

Modeling Understanding how to frame business problems as data science problems Navigating the full data science lifecycle: research and exploration, development, deployment, support Using correct ...

previous page

Showing results 41-60

All JobsMachine Learning Research JobsMachine Learning Research Jobs in Illinois

Machine Learning Research information

What is machine learning research?

Machine learning research is the scientific study and development of algorithms and statistical models that enable computers to perform tasks without explicit instructions, instead relying on patterns and inference. Researchers in this field work on advancing the theory, design, and application of machine learning systems, exploring areas such as deep learning, reinforcement learning, and unsupervised learning. They often publish their findings, develop new techniques, and collaborate with industry to solve real-world problems. This work is foundational to progress in artificial intelligence and has wide-ranging impacts across technology, healthcare, finance, and more.

What are the key skills and qualifications needed to thrive as a machine learning researcher?

To thrive as a Machine Learning Researcher, you need a strong background in mathematics, statistics, and computer science, often supported by an advanced degree (Master's or PhD) in a related field. Proficiency in programming languages like Python or R, experience with machine learning frameworks (such as TensorFlow or PyTorch), and familiarity with cloud computing platforms are typically required. Strong analytical thinking, creativity, and effective communication skills help researchers devise novel solutions and collaborate within multidisciplinary teams. These skills are essential for driving innovation, solving complex problems, and advancing the field of machine learning.

What are some common challenges faced by professionals in machine learning research and how can they be overcome?

One of the main challenges in Machine Learning Research is dealing with insufficient or poor-quality data, which can hinder model performance and generalizability. Additionally, keeping up with the rapid pace of advancements in the field requires continuous learning and adaptation. Collaborating effectively with multidisciplinary teams, such as data engineers and domain experts, is also crucial but can present communication challenges. Overcoming these obstacles typically involves building strong data pipelines, dedicating time for ongoing education, and honing collaboration and communication skills to bridge gaps between technical and non-technical stakeholders.

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

AspectMachine Learning ResearchData Scientist
Required CredentialsAdvanced degrees (Master's/PhD) in CS, ML, or related fieldsBachelor's or Master's in CS, Statistics, or related fields
Work EnvironmentResearch labs, academia, R&D departmentsBusiness environments, analytics teams, product development
Employer & Industry UsageTech companies, research institutions, universitiesTech, finance, healthcare, e-commerce, and more
Common Search & ComparisonYesYes

Machine Learning Research focuses on developing new algorithms and advancing theoretical understanding, often in academic or R&D settings. Data Scientists apply existing ML techniques to analyze data, build models, and generate insights for business decisions. While both roles require strong technical skills, Machine Learning Research emphasizes innovation and theory, whereas Data Scientists focus on practical application and data analysis.

How to become a machine learning researcher?

To become a machine learning researcher, typically a strong foundation in mathematics, statistics, and programming is required, along with advanced degrees such as a master's or Ph.D. in computer science, data science, or related fields. Gaining experience with machine learning frameworks like TensorFlow or PyTorch, publishing research, and staying current with academic literature are also important steps.

Is machine learning research a high paying job?

Machine learning research positions are generally well-paid due to the high demand for specialized skills in algorithms, data analysis, and programming languages like Python and TensorFlow. Salaries vary based on experience, education, and location, but they tend to be higher than average for many tech roles, especially in industry or academia with strong research funding.

What does a machine learning researcher do?

A machine learning researcher develops algorithms and models that enable computers to learn from data and improve their performance over time. They analyze large datasets, experiment with different techniques, and publish findings to advance the field, often using tools like Python, TensorFlow, or PyTorch. Their work typically involves both theoretical understanding and practical implementation to solve complex problems across various industries.

What are the most commonly searched types of Machine Learning Research jobs in Illinois?

The most popular types of Machine Learning Research jobs in Illinois are:

Machine Learning Research jobs near you
Infographic showing various Machine Learning Research job openings in Illinois as of August 2026, with employment types broken down into 1% As Needed, 80% Full Time, 18% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Machine Learning PhD Student Contributor

Mundelein, IL • On-site

Cobalt
See more jobs at Cobaltexternal

Other

Posted 9 days ago

Key responsibilities

  • Produce written reasoning traces on complex ML problems and draft expert reference answers to technical questions

  • Evaluate model-generated technical content by comparing responses, articulating strengths, and identifying points of failure in reasoning

  • Assess whether conclusions are supported by derivations, code, or experimental evidence and contribute to project guidelines and dataset development

Job description

About the role:

Cobalt is seeking PhD-qualified machine learning researchers with direct experience designing, running, and evaluating original ML research. This opportunity is suited to researchers who have worked in academic ML labs, industry research groups, or frontier lab environments, and who understand how technical claims are established, tested, and supported by evidence.

You may currently work, or have previously worked, as a PhD candidate, Postdoctoral Researcher, Research Scientist, Research Engineer, Applied Scientist, Member of Technical Staff, or in a related role.

You do not need prior experience in data annotation or model evaluation. You must, however, have contributed meaningfully to at least one substantive ML research output, and you must be comfortable reading papers, interpreting experimental results, and judging whether stated conclusions follow from the underlying evidence.


What you'll do:

Depending on the project, you may:

  • Produce written reasoning traces on hard ML problems, capturing how you reach a solution rather than only the solution itself, and draft expert reference answers to technical questions
  • Author novel problems in your subfield that have verifiable or defensible correct answers
  • Evaluate model-generated technical content: compare and rank responses, articulate what makes the stronger one stronger, and identify the specific step at which a chain of reasoning breaks down
  • Assess whether stated conclusions are supported by the underlying derivation, code, or experimental evidence
  • Design rubrics and partial-credit criteria for scoring multistep technical tasks, and contribute subject-matter expertise to benchmark and dataset development

Projects follow their own annotation guidelines and quality standards, and you will work with feedback from reviewers and lab research teams.


Required qualifications:

  • PhD, completed or in progress, in machine learning, computer science, statistics, mathematics, physics, or a closely related quantitative discipline, with research that is substantially ML focused
  • Direct experience authoring, co-authoring, or substantively contributing to at least one ML research output, such as a peer-reviewed paper, preprint, thesis chapter, or comparable technical artifact
  • Demonstrated depth in at least one area, for example optimization, reinforcement learning, language model training and post-training, learning theory, probabilistic methods, computer vision, natural language processing, or systems for ML
  • Ability to interpret papers, derivations, code and experimental results, and to explain your reasoning clearly in writing
  • Strong attention to detail, a commitment to factual accuracy, and the ability to work independently to agreed timelines


Why join Cobalt AI:

  • Advance frontier AI where it counts. Apply your research expertise to the data that frontier labs cannot obtain any other way, where your reasoning directly shapes how the next generation of models works through technical problems.
  • Grow professionally. Expand your influence through evaluation projects, advisory roles, and research collaborations, while deepening your understanding of how frontier models are trained and assessed.
  • Work with a top-tier network. Collaborate with researchers from leading institutions and labs on high-impact, flexible work.
  • Set your own schedule. Flexible 10 to 40 hour weeks that fit around your research position and your life.
  • Competitive pay. Rates vary by project and are determined by a number of factors, including scope, skillset, and experience.

Apply