1

Machine Learning Intern Jobs in Boulder, CO (NOW HIRING)

Intern

Loveland, CO ยท On-site

$15.50 - $20.50/hr

FCA Interns are collegiate volunteers who engage through FCA in a learning and developmental ... Loveland, CO Campus Department Intern June 2026-August 2026

ASL Student Intern

Denver, CO ยท On-site

$15.50 - $20.50/hr

Weare seeking a Student Intern in ASL Interpretation to support ourLanguage Servicesteam. This ... Learning & Development: Shadow professional interpreters, receive mentorship ...

Fall 2026 Intern - Treasury

Denver, CO ยท On-site

$15.75 - $20.75/hr

... learning opportunities that support ongoing professional development and career growth. The ... fax machine, printer Work Environment Typical office environment, adequately heated and cooled ...

Fall 2026 Intern - Treasury

Denver, CO ยท On-site

$15.75 - $20.75/hr

... learning opportunities that support ongoing professional development and career growth. The ... fax machine, printer Work Environment Typical office environment, adequately heated and cooled ...

Showing results 21-40

Machine Learning Intern information

See Boulder, CO salary details

$26.4K

$44.2K

$91.3K

How much do machine learning intern jobs pay per year?

As of Aug 9, 2026, the average yearly pay for machine learning intern in Boulder, CO is $44,163.00, according to ZipRecruiter salary data. Most workers in this role earn between $33,700.00 and $47,700.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive as a machine learning intern, and why are they important?

To thrive as a Machine Learning Intern, you need a solid understanding of statistics, programming (especially Python), and foundational machine learning concepts, typically supported by coursework or a degree in computer science or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and data analysis libraries, as well as experience with version control systems like Git, is highly valuable. Strong problem-solving skills, curiosity, and effective communication set outstanding candidates apart in this role. These abilities are essential for analyzing data, building models, and collaborating with teams to develop innovative AI solutions.

What does a machine learning intern do?

A Machine Learning Intern assists with developing, testing, and deploying machine learning models under the supervision of experienced data scientists or engineers. Their responsibilities may include data preprocessing, feature engineering, coding algorithms, analyzing results, and assisting with research tasks. Interns often work with programming languages like Python and libraries such as TensorFlow or PyTorch. The internship provides hands-on experience in real-world machine learning projects and helps interns build essential skills for a future career in the field.

What is the difference between Machine Learning Intern vs Data Science Intern?

AspectMachine Learning InternData Science Intern
Required CredentialsTypically pursuing or recent graduate in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually pursuing or recent graduate in Data Science, Statistics, or related fields; strong analytical and programming skills
Work EnvironmentTech companies, research labs, startups focusing on AI/ML projectsBusiness, finance, healthcare, and tech sectors analyzing data for insights
Employer & Industry UsageUsed in companies developing AI products, research institutions, tech startupsCommon in organizations requiring data analysis, reporting, and decision-making support

While both roles involve working with data and programming, a Machine Learning Intern focuses specifically on developing and implementing machine learning models, whereas a Data Science Intern works more broadly on analyzing data, creating reports, and deriving insights. The roles often overlap, but the Machine Learning Intern role emphasizes algorithm development and model deployment.

What types of projects do machine learning interns typically work on, and how are they supported by the team?

Machine Learning Interns often contribute to real-world projects such as data preprocessing, developing and testing models, or assisting with research for new algorithms. Interns are usually paired with a mentor or work within a small team, receiving guidance during code reviews and regular check-ins. This collaborative environment helps interns gain practical experience, quickly overcome challenges, and integrate feedback, ensuring a steep learning curve and valuable industry exposure.

What does a machine learning intern do?

A machine learning intern works in the field of data science. During an internship, you work alongside machine learning engineers who are developing artificial intelligence programs. They do this by writing computer code that allows a software system to run autonomously. Your exact responsibilities depend on the type and level of engineering that the company does. While you likely do not have coding duties, you may help the programmers test or debug their code. You may also work with algorithms and the mathematical aspects of artificial intelligence. A machine learning intern works under the supervision of a lead engineer.

What are the most commonly searched types of Machine Learning jobs in Boulder, CO? The most popular types of Machine Learning jobs in Boulder, CO are:
What are popular job titles related to Machine Learning Intern jobs in Boulder, CO? For Machine Learning Intern jobs in Boulder, CO, the most frequently searched job titles are:
What job categories do people searching Machine Learning Intern jobs in Boulder, CO look for? The top searched job categories for Machine Learning Intern jobs in Boulder, CO are:
What cities near Boulder, CO are hiring for Machine Learning Intern jobs? Cities near Boulder, CO with the most Machine Learning Intern job openings:
Infographic showing various Machine Learning Intern job openings in Boulder, CO as of August 2026, with employment types broken down into 14% Internship, 28% Full Time, 29% Part Time, and 29% Temporary. Highlights an 100% In-person job distribution, with an average salary of $44,163 per year, or $21.2 per hour.

Graduate Intern - LLM Reliability and Uncertainty for AI Science Assistants

The National Renewable Energy Laboratory (NREL)

Golden, CO โ€ข On-site

Full-time

Medical, Dental, Vision, Retirement

Posted 20 days ago


Job description

Posting Title
Graduate Intern - LLM Reliability and Uncertainty for AI Science Assistants
Location
CO - Golden
Position Type
Intern (Fixed Term)
Hours Per Week
40
Working at NLR
NLR is located at the foothills of the Rocky Mountains in Golden, Colorado is the nation's primary laboratory for energy systems research and development.
Join the National Laboratory of the Rockies (NLR), where world-class scientists, engineers, and experts are accelerating energy innovation through breakthrough research and systems integration. From our mission to our collaborative culture, NLR stands out in the research community for its commitment to an affordable and secure energy future. Spanning foundational science to applied systems engineering and analysis, we focus on solving complex challenges to deliver advanced, secure, reliable, and cost-effective energy solutions. Our work helps strengthen U.S. industries, support job creation, and promote national economic growth.
At NLR, you'll find a mission-driven environment supported by state-of-the-art facilities, multidisciplinary research teams, and strong collaborations with industry, academia, and other national laboratories. We offer robust professional development opportunities, and a competitive benefits package designed to support your career and well-being.
Job Description
The AI, Learning and Intelligent Systems group in the NLR Computational Science Center has an opening for a graduate student researcher in LLM Reliability and Uncertainty for AI Science Assistants. The researcher will investigate methods for quantifying uncertainty in LLM-based science assistants over multi-turn scientific dialogue, with an emphasis on flagging when a scientific question or task is underspecified or ill-posed. In practice, scientific questions can be vague, open-ended, or underdetermined. LLM-based assistants can quietly insert their own assumptions into such requests to fill the gap instead of raising concerns to their human counterpart. This internship will investigate if the assistant's internal representations can be probed to detect these instances so they may be flagged for the user or used to trigger clarifying questions. We are looking for a dynamic, motivated researcher with a strong technical background and an interest in AI for science, uncertainty-aware machine learning, human-AI scientific workflows, and trustworthy AI. The successful candidate must be able to work at the intersection of machine learning research and practical AI system integration.
Responsibilities include:
  • Research and evaluate uncertainty quantification and hallucination detection methods for multi-turn, agentic scientific workflows
  • Develop probing methods that predict, from a model's internal representations, when a scientific task specification is incomplete or inconsistent and a clarifying question is warranted
  • Build and instrument evaluation pipelines that capture and analyze model internal states over multi-turn scientific dialogue on HPC systems
  • Conduct experiments and analyze model behavior across computational science domains and established benchmarks
  • Contribute to technical documentation, research reports, publications, and presentations summarizing project progress and findings
  • Develop, test, and maintain high-quality research code and evaluation pipelines

Basic Qualifications
Minimum of a 3.0 cumulative grade point average.
Undergraduate: Must be enrolled as a full-time student in a bachelor's degree program from an accredited institution.
Post Undergraduate: Earned a bachelor's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate: Must be enrolled as a full-time student in a master's degree program from an accredited institution.
Post Graduate: Earned a master's degree within the past 12 months. Eligible for an internship period of up to one year.
Graduate + PhD: Completed master's degree and enrolled as PhD student from an accredited institution.
Please Note:
โ€ข Applicants are responsible for uploading official or unofficial school transcripts, as part of the application process.
โ€ข If selected for position, a letter of recommendation will be required as part of the hiring process.
โ€ข Must meet educational requirements prior to employment start date.
* Must meet educational requirements prior to employment start date.
Additional Required Qualifications
  • Familiarity with large language models, including agentic, tool-using, or multi-turn conversational LLM systems
  • Experience developing or evaluating machine learning models for classification, uncertainty estimation, or related tasks
  • Knowledge of probabilistic machine learning or uncertainty quantification concepts
  • Hands-on experience with open-weight LLMs and modern deep learning frameworks
  • Experience running Python code on HPC or multi-GPU systems
  • Strong software engineering and debugging skills
  • Ability to work independently while collaborating effectively in a multidisciplinary research environment

Preferred Qualifications
  • Research experience related to hallucination detection, uncertainty quantification, interpretability, explainability, or trustworthy AI
  • Familiarity with representation probing or mechanistic interpretability methods
  • Experience with LLM benchmarking and evaluation, including multi-turn or conversational agent evaluation and LLM-as-a-judge protocols
  • Experience with scientific question-answering systems, AI for science applications, or scientific agent frameworks
  • Coursework or research background in a computational science domain (e.g., fluid mechanics, solid mechanics, materials science, or numerical methods for PDEs)

Job Application Submission Window
The anticipated closing window for application submission is up to 30 days and may be extended as needed.
Annual Salary Range (based on full-time 40 hours per week)
Job Profile: / Annual Salary Range: $44,500 - $71,200
NLR takes into consideration a candidate's education, training, and experience, expected quality and quantity of work, required travel (if any), external market and internal value, including seniority and merit systems, and internal pay alignment when determining the salary level for potential new employees. In compliance with the Colorado Equal Pay for Equal Work Act, a potential new employee's salary history will not be used in compensation decisions.
Benefits Summary
Benefits include medical, dental, and vision insurance; 403(b) Employee Savings Plan with employer match*; and sick leave (where required by law). NLR employees may be eligible for, but are not guaranteed, performance-, merit-, and achievement- based awards that include a monetary component. Some positions may be eligible for relocation expense reimbursement. Internships projected to be less than 20 hours per week are not eligible for medical, dental, or vision benefits.
* Based on eligibility rules
Badging Requirement
NLR is subject to Department of Energy (DOE) access restrictions. All employees must also be able to obtain and maintain a federal Personal Identity Verification (PIV) card as required by Homeland Security Presidential Directive 12 (HSPD-12), which includes a favorable background investigation. Intern assignments extending beyond six months will be subject to this requirement.
Drug Free Workplace
NLR is committed to maintaining a drug-free workplace in accordance with the federal Drug-Free Workplace Act and complies with federal laws prohibiting the possession and use of illegal drugs. Under federal law, marijuana remains an illegal drug.
If you are offered employment at NLR, you must pass a pre-employment drug test prior to commencing employment. Unless prohibited by state or local law, the pre-employment drug test will include marijuana. If you test positive on the pre-employment drug test, your offer of employment may be withdrawn.
Submission Guidelines
Please note that in order to be considered an applicant for any position at NLR you must submit an application form for each position for which you believe you are qualified. Applications are not kept on file for future positions. Please include a cover letter and resume with each position application.
Equal Opportunity Employer
All qualified applicants will receive consideration for employment without regard basis of age (40 and over), color, disability, gender identity, genetic information, marital status, domestic partner status, military or veteran status, national origin/ancestry, race, religion, creed, sex (including pregnancy, childbirth, breastfeeding), sexual orientation, and any other applicable status protected by federal, state, or local laws.
Reasonable Accommodations
E-Verify www.dhs.gov/E-Verify For information about right to work, click here for English or here for Spanish.
E-Verify is a registered trademark of the U.S. Department of Homeland Security. This business uses E-Verify in its hiring practices to achieve a lawful workforce.