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Junior Machine Learning Jobs in Illinois (NOW HIRING)

IMC Trading is seeking a Machine Learning Research Lead with proven experience applying ... Mentor junior researchers and contribute to a culture of research excellence and experimentation

Machine Learning Research Lead

Chicago, IL · On-site

$250K - $300K/yr

  • PTO

IMC Trading is seeking a Machine Learning Research Lead with proven experience applying ... Mentor junior researchers and contribute to a culture of research excellence and experimentation

Senior AI Machine Learning Engineer

Chicago, IL · Hybrid

$126K - $166K/yr

As a Senior Machine Learning Engineer , you will play a critical role in designing, building, and ... Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable ...

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... Work with junior engineers and peers to provide mentorship and thought leadership. Be comfortable ...

Machine Learning Platform Engineer

Chicago, IL

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

... machine learning and scientific computing. * Provide oversight and hands-on support for the ... Participate in interviewing and evaluation of new talent, mentoring and training of junior ...

The Hartfordis seeking aSenior AI Machine Learning Engineerwithin Employee Benefits Applied AI and ... Guide and mentor junior engineers by breaking down technical work, reviewing code, explaining model ...

Junior HPC Applications Engineer

Chicago, IL · On-site +1

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

About the role Parallel Works is hiring a Junior HPC Applications Engineer to support the ... It suits someone who has run scientific or machine learning workloads on a cluster as a user and ...

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Junior Machine Learning information

See Illinois salary details

$7

$26

$45

How much do junior machine learning jobs pay per hour?

As of Aug 19, 2026, the average hourly pay for junior machine learning in Illinois is $26.12, according to ZipRecruiter salary data. Most workers in this role earn between $15.82 and $32.16 per hour, depending on experience, location, and employer.

What does a junior machine learning engineer do?

A Junior Machine Learning Engineer assists in the development and implementation of machine learning models and algorithms under the supervision of more experienced engineers. They typically help with data collection, cleaning, feature engineering, model training, and evaluation. Junior engineers may also write code, test prototypes, and contribute to improving model performance while learning best practices in the field. Their role often involves collaborating with data scientists and software engineers to integrate machine learning solutions into products or services.

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

To thrive as a Junior Machine Learning Engineer, you need a solid understanding of programming (especially Python), basic statistics, linear algebra, and familiarity with machine learning concepts, typically supported by a relevant degree or coursework. Proficiency in tools and frameworks like scikit-learn, TensorFlow, PyTorch, and version control systems such as Git is often expected. Strong problem-solving abilities, curiosity, and effective communication are crucial soft skills for collaborating with teams and explaining technical concepts. These skills and qualities are important because they enable you to contribute effectively to building, testing, and improving machine learning models in real-world applications.

What types of projects and tasks can a junior machine learning professional typically expect to work on in their first year?

As a Junior Machine Learning professional, you’ll often support senior data scientists and engineers by preparing data, implementing basic algorithms, and assisting with model evaluation. Your daily tasks may include data cleaning, feature engineering, running experiments, and writing code to automate data pipelines. You might also help document processes and present your findings to team members. While the work is often collaborative, you’ll have opportunities to take ownership of smaller projects and progressively contribute to larger initiatives as you gain experience.

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

AspectJunior Machine LearningData Scientist
Required CredentialsBachelor's in CS, Data Science, or related field; some experience with ML toolsBachelor's or Master's in CS, Statistics, or related; strong programming and statistical skills
Work EnvironmentEntry-level projects, supervised tasks, team collaborationAdvanced analysis, model development, cross-functional teams
Industry UsageCommon in tech companies, startups, research labsWidespread across industries like finance, healthcare, tech

Junior Machine Learning roles focus on foundational ML tasks and learning on the job, while Data Scientists handle complex data analysis, model building, and strategic insights. The roles differ mainly in experience level and scope of responsibilities, but both require strong technical skills and familiarity with data tools.

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

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

What cities in Illinois are hiring for Junior Machine Learning jobs?

Cities in Illinois with the most Junior Machine Learning job openings:

Infographic showing various Junior Machine Learning 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, with an average salary of $54,332 per year, or $26.1 per hour.

Machine Learning Engineer

University of Illinois

Champaign, IL • On-site

Other

Posted 5 days ago


Job description

About Dow
At Dow, we believe in putting people first and we're passionate about delivering integrity, respect and safety to our customers, our employees and the planet.
Our people are at the heart of our solutions. They reflect the communities we live in and the world where we do business. Their diversity is our strength. We're a community of relentless problem solvers that offers the daily opportunity to contribute with your perspective, transform industries and shape the future. Our purpose is simple - to deliver a sustainable future for the world through science and collaboration. If you're looking for a challenge and meaningful role, you're in the right place.
About this role
Dow has an exciting and challenging opportunity for a Machine Learning Engineer within our Enterprise Data & Analytics organization located in Houston, TX; Midland, MI; or Champaign, IL (Dow Delivery Center at UIUC). (Please note the posting indicates other locations, but the site location is in CHAMPAIGN, IL.)
As a Machine Learning Engineer in our Data & Analytics Platforms team specializing in data and analytics solutions, you will work with a cross-functional team whose objective is to deliver solutions that drive business value for Dow. In this role, you will work closely with data engineers, data scientists, domain experts, and software engineers to design, develop, and deploy machine learning systems, including training and inference pipelines on the Azure Databricks platform. You will also help drive a culture around setting standards and adopting best practices for machine learning and MLOps across the organization.
  • This position does not offer relocation assistance
  • This position does not have people leadership responsibility. This position is an Independent Contributor; however, you may act as coach and mentor to junior resources
Requirements
  • A minimum of a Bachelor's degree, or 8 years relevant experience, or relevant military experience at an E6 rank/Petty Officer 2nd Class or higher is required
  • A minimum of 3 years of experience developing solutions in machine learning, data science, or related field
  • A minimum requirement for this U.S. based position is the ability to work legally in the United States. No visa sponsorship/support is available for this position, including for any type of U.S. permanent residency () process

Preferred
  • A degree in computer science, engineering, mathematics, statistics, data science or related field
  • Proficient in Python and one or more machine learning frameworks such as TensorFlow, PyTorch, Scikit-learn, etc
  • Experience in developing and deploying machine learning models and pipelines on the Databricks platform using Databricks MLflow, Delta Lake, SQL Analytics, Model Registry, Jobs, and Workspace
  • Strong knowledge of machine learning concepts, techniques, and algorithms
  • Ability to perform data analysis, feature engineering, model selection, optimization, and evaluation using Databricks
  • Ability to communicate complex machine learning concepts and results to technical and non-technical audiences using Databricks notebooks and dashboards
  • Ability to work independently and collaboratively in a fast-paced and dynamic environment
  • Curiosity and passion for learning new machine learning skills and technologies using Databricks
  • Strong knowledge of data modeling, data warehousing, and ETL processes
  • Experience designing and deploying into production both traditional and generative AI systems
  • Proficiency in SQL and experience with big data technologies such as Apache Spark and Hive
  • Experience working within Azure Machine Learning
  • Experience containerizing and deploying ML models to Azure Kubernetes Service
  • Experience with Azure Data Factory, Azure Data Lake Storage Gen2, and other Azure services
  • Multi-application and cross-platform design experience
  • Understanding of data lakehouse platform design and associated workflows
  • Ability to thrive in challenging situations and solve complex problems
  • Ability to manage own work effort in multiple projects with little supervision
  • Interested in emerging technologies with the ability to quickly learn and exploit cutting edge offerings to achieve business objectives
Responsibilities
  • Designs and implements pipelines and other workflow infrastructure to meet the requirements for new AI/ML solutions that involve online, batch, or real-time inference
  • Deploys and monitors machine learning models in production using Databricks Model Registry, Jobs, and Workspace
  • Frequently collaborates with data engineers, DevOps/platform engineers, data scientists, and domain experts as part of a comprehensive MLOps framework to ensure AI/ML solutions are performant, reliable, and maintainable
  • Works frequently with application development teams to ensure seamless integrations
  • Works proficiently with various ML frameworks, such as scikit-learn, TensorFlow, PyTorch, Keras, as well as distributed frameworks like Spark MLlib and Ray
  • Performs data analysis, feature engineering, model selection, hyperparameter optimization, and model evaluation using Databricks MLFlow, Delta Lake, and SQL Analytics and other tools as part of the end-to-end ML lifecycle
  • Researches and implements new machine learning techniques and methods using Databricks, staying abreast of the latest trends and technologies
  • Documents and communicates machine learning results and insights to stakeholders using Databricks notebooks and dashboards
  • Understands IT security policies and implements them as part of new solution designs
  • Follows and promotes the best practices and standards for machine learning and MLOps across the organization using Databricks and Azure DevOps

Your skills:
  • Solutions Delivery: End-to-end ownership of Azure data solutions-translating ambiguous business needs into robust architectural blueprints, then delivering through design, build, test, deployment, and post-launch monitoring with a focus on reliability, performance, and cost efficiency.
  • Cloud Computing: Designing and operating cloud-native architectures on Azure (e.g., Databricks Lakehouse, ADF/Workflows, Functions, Logic Apps, Azure SQL) with CI/CD and IaC to scale securely and economically for ML, BI, streaming, and web applications.
  • Integration Services: Building secure, high-throughput integrations-REST APIs and event/stream pipelines (e.g., Event Hubs/Kafka)-to connect polyglot data stores (SQL Server, Cosmos DB, Neo4j) and enable real-time and batch data products.
  • Security Awareness: Embedding governance, identity, and compliance into the architecture (OAuth/RBAC, data governance, re-authorization/ownership verification), enforcing code reviews and automated controls across pipelines and deployments.
  • Strategic Planning: Aligning platform roadmaps and technology choices with enterprise strategy, mentoring engineers on best practices, defining standards and KPIs, and prioritizing modernization and cost-optimization initiatives that maximize business impact.

Please use this link to apply: Machine Learning Engineer - Dow

University of Illinois logo

About University of Illinois

Sourced by ZipRecruiter

The University of Illinois, located in Urbana, Illinois, US, is a prominent entity in the higher education sector. Operating its official functions through its website uillinois.edu, the institution provides a range of educational programs and services. The University was founded in 1867 and has since grown dramatically both in size and reputation. Its core values are embodied in its mission to enhance the lives of its students and citizens in the state, nation, and world through leadership in learning, discovery, engagement, and economic development. The university boasts several notable achievements including producing Nobel laureates and Pulitzer prize winners. It is renowned for its research programs and is known for significant advancements across various fields including engineering, science, and humanities.

Industry

Colleges, universities, and professional schools

Company size

5,001 - 10,000 Employees

Headquarters location

Urbana, IL, US

Year founded

1974

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