AI/Machine Learning, Summer Intern (Hybrid)
About The Position
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.
Requirements
- 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.
- Demonstrated experience building AI applications — whether through coursework, personal projects, open-source contributions, or prior internships.
- Proficiency in Python with hands-on experience using ML libraries such as NumPy, Pandas, scikit-learn, PyTorch, or TensorFlow.
- Experience working with LLM/GenAI platforms (e.g., OpenAI API, Anthropic Claude, LangChain, RAG pipelines, or prompt engineering).
- Familiarity with cloud platforms (AWS, Azure, or GCP) and data tools including SQL and data pipeline or dashboard tooling.
- Strong written and verbal communication skills; able to present technical concepts clearly to both technical peers and non-technical stakeholders.
- Self-starter with the ability to move fast, iterate, and learn from ambiguous, real-world data problems.
Nice To Haves
- 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.
Responsibilities
- 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.
Benefits
- Paid – $17/hour
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What This Job Offers
Job Type
Full-time
Career Level
Intern
