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Machine Learning Engineer Intern Jobs in Evanston, IL

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off-sites * Equipment and learning budget to help you do your best work and keep up with ...

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and offsites * Equipment and learning budget to help you do your best work and keep up with the ...

Albi

Senior Machine Learning Engineer (LLMs)

Chicago, IL · On-site

$126K - $166K/yr

... engineers * An environment that values deep work, clear thinking, and real impact * Regular team events and off‑sites * Equipment and learning budget to help you do your best work and keep up with ...

IMC Trading

Machine Learning Researcher

Chicago, IL · On-site

The role involves designing and deploying machine learning models, collaborating with trading teams ... Required : • PhD or Master's in Engineering, Math, Statistics, Computer Science, or related ...

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Showing results 1-20

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

Machine Learning Engineer Intern information

See Evanston, IL salary details

$24.5K

$40.9K

$84.5K

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

As of Jul 9, 2026, the average yearly pay for machine learning engineer intern in Evanston, IL is $40,866.00, according to ZipRecruiter salary data. Most workers in this role earn between $31,200.00 and $44,100.00 per year, depending on experience, location, and employer.

What types of projects and tasks do Machine Learning Engineer Interns typically work on?

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 is a Machine Learning Engineer Intern job?

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 are the key skills and qualifications needed to thrive in the Machine Learning Engineer Intern position, and why are they important?

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.

What are the most commonly searched types of Machine Learning Engineer jobs in Evanston, IL? The most popular types of Machine Learning Engineer jobs in Evanston, IL are:
What are popular job titles related to Machine Learning Engineer Intern jobs in Evanston, IL? For Machine Learning Engineer Intern jobs in Evanston, IL, the most frequently searched job titles are:
What job categories do people searching Machine Learning Engineer Intern jobs in Evanston, IL look for? The top searched job categories for Machine Learning Engineer Intern jobs in Evanston, IL are:
What cities near Evanston, IL are hiring for Machine Learning Engineer Intern jobs? Cities near Evanston, IL with the most Machine Learning Engineer Intern job openings:
Machine Learning Engineer Intern jobs near you
Infographic showing various Machine Learning Engineer Intern job openings in Evanston, IL as of July 2026, with employment types broken down into 87% Full Time, 10% Part Time, 2% Contract, and 1% Nights. Highlights an 87% Physical, 4% Hybrid, and 9% Remote job distribution, with an average salary of $40,866 per year, or $19.6 per hour.
Staff/Senior Machine Learning Engineer, Clinical AI

Staff/Senior Machine Learning Engineer, Clinical AI

Tempus

Chicago, IL • On-site, Remote

$170K - $230K/yr

Full-time

Re-posted 23 days ago

Job description

Passionate about precision medicine and advancing the healthcare industry?

Recent advancements in underlying technology have finally made it possible for AI to impact clinical care in a meaningful way. Tempus' proprietary platform connects an entire ecosystem of real-world evidence to deliver real-time, actionable insights to physicians, providing critical information about the right treatments for the right patients, at the right time.

We're seeking a highly skilled and innovative Staff/Senior Machine Learning Engineer to join our Clinical AI Team. As a Staff/Senior Machine Learning Engineer, you'll play a crucial role in leveraging and deploying cutting-edge natural language processing models and LLMs specifically tailored for healthcare applications at scale. Your work will contribute to optimizing clinical workflows, improving clinical trial matching, and advancing medical research. This position offers an exciting opportunity to leverage the power of natural language processing and LLMs to revolutionize healthcare and make a significant impact on people's lives.

What You Will Do:

  • Build and operate production AI pipelines: LLM-powered extraction, batch orchestration, and inference, with a focus on reliability, cost, and latency

  • Design and maintain Airflow-based orchestration for batch clinical workflows

  • Build the observability (metrics, logging, alerting) that catches regressions before they reach downstream consumers

  • Build and maintain eval infrastructure that measures clinical model output quality continuously: regression detection, drift, gold-set management, dashboards

  • Ship platform tooling and SDKs that accelerate Machine Learning Scientists and downstream consumers

  • Partner with Machine Learning Scientists to debug bad model outputs to root cause (data, prompt, or pipeline)

  • Participate in the pod's on-call rotation

  • Collaborate with platform / infrastructure teams to leverage GCP services for performance, security, and cost-efficiency

  • Author and review design docs for cross-pod work

  • Raise the engineering bar through code review and design review

Required Qualifications:

  • Strong command of Python in production environments

  • Experience designing, building, and integrating with microservices in production

  • Deployed data orchestration workflows in production (Airflow or equivalent)

  • Worked on cloud-native services (GCP preferred but not required)

  • Built monitoring, observability, and alerting for production systems

  • Hands-on experience with at least one major ML framework - we primarily use LangGraph; PyTorch, spaCy, or equivalents are equally welcome

  • Strong written and verbal communication, including experience authoring and reviewing design docs (RFCs, PRDs, or equivalent); partners well with research scientists, PMs, and clinicians

Preferred Qualifications:

  • Operated production systems hands-on - on-call rotations, incident response, postmortems

  • Experience building eval / quality measurement systems for ML or LLM outputs

  • Hands-on production LLM application experience (prompts, agents, RAG, LLM evals, extraction pipelines)

  • Built internal platforms or SDKs that other engineers / scientists depended on

  • Experience working with clinical or biomedical data (EHR, genomics, pathology, clinical notes)

  • Contributions to relevant open-source projects

#LI-BL1

New York Pay Range - $170,000-$230,000USD

California Pay Range - $170,000-$230,000USD

Illinois Pay Range - $150,000-$210,000USD

Remote - USA Range - $150,000-$210,000USD

The expected salary range above is applicable if the role is performed from California and may vary for other locations (Colorado, Illinois, New York). Actual salary may vary based on qualifications and experience. Tempus offers a full range of benefits, which may include incentive compensation, restricted stock units, medical and other benefits depending on the position.

Additionally,for remote roles open to individuals in unincorporated Los Angeles - including remote roles-Tempus reasonably believes that criminal history may have a direct, adverse and negative relationship on the following job duties, potentially resulting in the withdrawal of the conditional offer of employment: engaging positively with customers and other employees; accessing confidential information, including intellectual property, trade secrets, and protected health information; and appropriately handling such information in accordance with legal and ethical standards. Qualified applicants with arrest or conviction records will be considered for employment in accordance with applicable law, including the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act.

We are an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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