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Machine Learning Winter Internship Jobs in Colorado

True Anomaly

Machine Learning Engineer

Denver, CO · On-site

$85K - $180K/yr

Bachelor's degree in computer science, machine learning, data science, electrical engineering, or a ... Internship, research, or project experience applying ML to real-world or research datasets

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Machine Learning Winter Internship information

What are the key skills and qualifications needed to thrive as a Machine Learning Winter Intern, and why are they important?

To thrive as a Machine Learning Winter Intern, you generally need a solid foundation in mathematics, programming (especially Python), and a basic understanding of machine learning concepts, often acquired through coursework or relevant projects. Familiarity with tools such as TensorFlow, PyTorch, and data analysis libraries like Pandas and NumPy is typically required. Strong problem-solving abilities, collaboration, and curiosity help interns stand out in team-based, fast-paced environments. These skills are crucial for effectively contributing to real-world projects and quickly learning from experienced professionals during the internship.

What types of projects and tasks can I expect to work on during a Machine Learning Winter Internship?

During a Machine Learning Winter Internship, you can expect to work on hands-on projects such as data preprocessing, building and evaluating machine learning models, and assisting with research experiments. Interns often contribute to real-world applications, such as developing predictive analytics tools, optimizing algorithms, or supporting deployment efforts. Collaboration is common, as you'll work closely with data scientists, engineers, and sometimes product teams, giving you exposure to the full machine learning workflow. This environment provides an excellent opportunity to apply theoretical knowledge, gain practical experience, and build a professional network in the field.

What is a Machine Learning Winter Internship?

A Machine Learning Winter Internship is a short-term, practical training program typically offered during the winter months for students or early-career professionals interested in machine learning. Interns work on real-world projects involving data analysis, model development, and algorithm implementation under the guidance of experienced mentors. The internship provides hands-on experience with tools and techniques used in the field, helping participants build technical skills and gain industry exposure. These positions are often offered by tech companies, research labs, or startups and can be either remote or onsite. Successful completion of a machine learning internship can enhance a candidate's resume and open up further career opportunities in artificial intelligence and data science.

What is the difference between Machine Learning Winter Internship vs Data Science Winter Internship?

AspectMachine Learning Winter InternshipData Science Winter Internship
Required CredentialsUndergraduate or graduate in CS, AI, or related fields; some knowledge of ML frameworksUndergraduate or graduate in Statistics, Math, CS; familiarity with data analysis tools
Work EnvironmentResearch labs, tech companies, startups focusing on ML modelsData analysis, visualization, and interpretation in various industries
Employer & Industry UsageTech firms, AI startups, research institutionsTech companies, finance, healthcare, consulting

While both internships involve working with data, the Machine Learning Winter Internship emphasizes developing and applying ML algorithms, whereas the Data Science Winter Internship focuses on analyzing data, creating reports, and deriving insights. Candidates should choose based on their specific skills and career goals in AI or data analysis.

What are popular job titles related to Machine Learning Winter Internship jobs in Colorado? For Machine Learning Winter Internship jobs in Colorado, the most frequently searched job titles are:
What job categories do people searching Machine Learning Winter Internship jobs in Colorado look for? The top searched job categories for Machine Learning Winter Internship jobs in Colorado are:
What cities in Colorado are hiring for Machine Learning Winter Internship jobs? Cities in Colorado with the most Machine Learning Winter Internship job openings:
Machine Learning Winter Internship jobs near you

AI/Machine Learning, Summer Intern (Hybrid)

accuris

Denver, CO

$17/hr

Other

Posted 23 hours ago

Job description

AI/Machine Learning Summer Intern Supply Chain Intelligence | Accuris

Division: Supply Chain Intelligence

Level: Undergraduate (Junior/Senior) or Graduate (MS/MBA) 

Location: Denver, CO – Hybrid (3 days on-site per week)

Duration: June 1 – August 3–10, 2026 | 9–10 weeks

Compensation: Paid – $17/hour

ABOUT THE ROLE

Accuris's Supply Chain Intelligence division is transforming how engineers, procurement teams, and sustainability leaders understand the global electronics supply chain. We are looking for a creative, technically strong AI/ML Summer Intern to join our team and help build the next generation of AI-powered capabilities — from carbon footprint calculators for electronic components to predictive algorithms for supply chain risk and availability.

This is a hands-on, build-first internship. You will go from idea to working prototype, collaborating closely with product managers, engineers, and data scientists. By the end of the summer, you will have shipped a real AI tool and presented it to audiences ranging from engineers to senior executives.

WHAT YOU'LL WORK ON

  • Design and build AI-powered prototypes such as carbon footprint calculators for electronic components or predictive models for supply chain risk, demand, and component availability.
  • Apply LLM and generative AI techniques to create intelligent, data-driven tools using platforms like OpenAI, Anthropic Claude, or LangChain.
  • Develop and validate machine learning models using Python and standard ML libraries (scikit-learn, PyTorch, TensorFlow, etc.).
  • Work with cloud-based data pipelines, SQL databases, and dashboards to source and transform supply chain data.
  • Use rapid "vibe coding" methodologies to iterate quickly on AI concepts and validate ideas early.
  • Translate your technical work into clear, compelling presentations for both engineering teams and executive audiences.

WHAT YOU'LL DELIVER

By the end of the summer, you will be expected to deliver two things:

  • A working AI prototype — a functional tool or model that demonstrates clear value against a supply chain intelligence use case (e.g., component carbon footprint estimator, predictive availability scorer, or similar).
  • An executive-ready presentation — a polished deck communicating your approach, methodology, findings, and recommended next steps for the business.

REQUIRED QUALIFICATIONS

  1. Currently enrolled as a Junior or Senior undergraduate, or a Graduate (MS or MBA) student in Computer Science, Data Science, Electrical Engineering, Information Systems, or a related field.
  2. Demonstrated experience building AI applications — whether through coursework, personal projects, open-source contributions, or prior internships.
  3. Proficiency in Python with hands-on experience using ML libraries such as NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow.
  4. Experience working with LLM/GenAI platforms (e.g., OpenAI API, Anthropic Claude, LangChain, RAG pipelines, or prompt engineering).
  5. Familiarity with cloud platforms (AWS, Azure, or GCP) and data tools including SQL and data pipeline or dashboard tooling.
  6. Strong written and verbal communication skills; able to present technical concepts clearly to both technical peers and non-technical stakeholders.
  7. Self-starter with the ability to move fast, iterate, and learn from ambiguous, real-world data problems.

PREFERRED QUALIFICATIONS

  • Prior exposure to supply chain, electronics manufacturing, procurement, or sustainability/ESG domains.
  • Familiarity with carbon accounting frameworks, life cycle assessment (LCA), or sustainability data (e.g., GHG Protocol, Scope 3 emissions).
  • Experience building and evaluating predictive models for time-series, classification, or regression problems.
  • Active portfolio of AI/ML projects (e.g., GitHub, Kaggle, Hugging Face, or personal website).
  • Comfort with rapid prototyping and "vibe coding" — the ability to quickly scaffold and iterate on AI-driven tools.

ABOUT ACCURIS

Accuris provides engineers, procurement specialists, and product teams with trusted data and intelligence to design better products and build more resilient supply chains. Our Supply Chain Intelligence division delivers real-time component data, risk analytics, and predictive insights to help global organizations make faster, smarter sourcing decisions. This internship puts you at the frontier of AI applied to one of the world's most complex and consequential industries.

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