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Machine Learning Research Jobs in Illinois (NOW HIRING)

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Whiterabbit.ai

Learn and understand a large body of research in deep learning and machine learning * Participate in cutting-edge research for medical applications of computer vision Must Have Experience

Gotion, Inc.

Machine Learning Engineer

Manteno, IL · On-site

You will collaborate closely with cross-disciplinary R&D teams to develop and deploy machine learning solutions that address real-world challenges in advanced materials, electrochemical systems, and ...

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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.

Research Scientist Intern (2025)

Joliet, IL • On-site

Whiterabbit.ai
Software Development • 51 - 200 employees
Learn more about Whiterabbit.aiexternal

Other

Re-posted 19 days ago

Job description

We are looking for a Research Scientist Intern to push the state of the art of our AI models. As a Research Scientist Intern at Whiterabbit.ai, you will:

  • Play a key role in architecting the algorithms and models that will power our products
  • Train on a dedicated high-performance compute cluster specialized for deep learning research
  • Work with doctors and healthcare professionals to identify serious problems and leverage their domain expertise to build robust solutions
  • Remain an active contributor to the research community by partnering with universities and publishing high impact papers

Who we are:

Our mission at Whiterabbit.ai is to save lives and eliminate suffering through the early detection of cancer with artificial intelligence. We collaborate closely with one of the top medical schools in the country and have exclusive access to one of the world’s largest cancer datasets with millions of images. We invent algorithms that make doctors more productive, more accurate, and more capable. We build products and services with a relentless focus on transforming the patient’s healthcare experience.

Responsibilities

  • Develop highly scalable classifiers and detectors that solve real-world problems
  • Learn and understand a large body of research in deep learning and machine learning
  • Participate in cutting-edge research for medical applications of computer vision

Must Have Experience

  • Experience with deep learning and convolutional networks
  • Strong theoretical and empirical research background
  • Fluency with a deep learning framework and Python

Nice to Have Experience

  • Contributions to research communities and efforts, such as publications at conferences like CVPR, NeurIPS, ICCV, ECCV, ICML, and ICLR
  • Large scale machine learning experience working with terabytes of data
  • Implemented custom operations/modules in a deep learning framework
  • Imagination, ambition, and curiosity

Apply