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

AspectHourly Machine Learning InternHourly Data Science Intern
Required CredentialsTypically pursuing or holding a degree in Computer Science, Data Science, or related fields; knowledge of programming and ML frameworksUsually enrolled in or graduated from a program in Data Science, Statistics, or related areas; proficiency in data analysis tools
Work EnvironmentTech companies, startups, research labs focusing on ML model developmentOrganizations applying data analysis to business problems, often in tech, finance, or healthcare sectors
Employer & Industry UsageCommonly used in AI/ML-focused roles within tech industriesWidely used across industries for data-driven decision making

The Hourly Machine Learning Intern focuses on developing and testing machine learning models, requiring programming and ML-specific skills. In contrast, the Hourly Data Science Intern emphasizes analyzing data to extract insights, often involving statistical analysis and data visualization. Both roles are valuable entry points in data-related fields but differ in technical focus and daily tasks.

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Infographic showing various Hourly Machine Learning Intern job openings in Colorado as of May 2026, with employment types broken down into 90% Full Time, 7% Part Time, and 3% Contract. Highlights an 75% Physical, and 25% Remote job distribution.

AI/Machine Learning, Summer Intern (Hybrid)

accuris

Denver, CO

$17/hr

Other

Posted yesterday

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.

Apply