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Machine Learning Engineer Intern Jobs in Urbana, IL

Varsity Tutors

Machine Learning Tutor

Champaign, IL · Remote

$18 - $40/hr

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

CIT Trucks

Truck Sales Intern

Champaign, IL · On-site

$15.50 - $17.25/hr

Responsibilities of a Truck Sales Intern entail: * Conducting regular sales calls ranging from ... Engineering and selling products at profit levels established by CIT Trucks * Effectively ...

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All JobsMachine Learning Engineer Intern JobsMachine Learning Engineer Intern Jobs in Urbana, IL

Machine Learning Engineer Intern information

See Urbana, IL salary details

$25.7K

$42.9K

$88.6K

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

As of Aug 20, 2026, the average yearly pay for machine learning engineer intern in Urbana, IL is $42,858.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,700.00 and $46,300.00 per year, depending on experience, location, and employer.

What is a machine learning engineer intern?

A Machine Learning Engineer Intern is a temporary, entry-level role where individuals work with data scientists and engineers to develop, test, and optimize machine learning models. Interns typically assist in data preprocessing, feature engineering, model training, and evaluation. They may also work on improving existing algorithms, implementing research papers, or deploying models into production. This role provides hands-on experience with machine learning frameworks such as TensorFlow and PyTorch, as well as coding in Python and working with large datasets. The internship helps build practical skills and industry experience in artificial intelligence and data science.

What do machine learning engineer interns do?

Machine Learning Engineer Interns are often involved in data preparation, feature engineering, model development, and performance evaluation under the guidance of senior engineers or data scientists. You may help implement and test machine learning algorithms, assist in cleaning and visualizing datasets, and contribute to code reviews or research tasks. Interns frequently collaborate with cross-functional teams, such as data scientists, software engineers, and product managers, to solve real-world problems and support ongoing projects. This hands-on experience provides valuable insights into the practical application of machine learning in a professional setting.

What skills and qualifications are needed to thrive as a machine learning engineer intern?

To thrive as a Machine Learning Engineer Intern, you need a solid understanding of programming languages such as Python, knowledge of machine learning algorithms, and experience with data analysis, typically supported by coursework in computer science or related fields. Familiarity with tools like TensorFlow, PyTorch, scikit-learn, and version control systems such as Git is often required. Strong problem-solving abilities, attention to detail, and effective communication are valuable soft skills in this role. These competencies enable interns to contribute meaningfully to projects, collaborate efficiently with teams, and adapt in a fast-paced, tech-driven environment.

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Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Urbana, IL as of August 2026, with employment types broken down into 1% As Needed, 72% Full Time, 26% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $42,858 per year, or $20.6 per hour.

Machine Learning Engineer

University of Illinois

Champaign, IL • On-site

Other

This job post has expired today. Applications are no longer accepted.

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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