Position Overview: As an AI Engineer Intern, you'll work directly with business stakeholders, scientists, and engineers to design and ship AI-powered tools that improve how we operate, communicate, and make decisions across the mining and processing business unit.
This is not a research role. You'll be building things that go into production and get used by real people on real projects. If you've shipped something with LLMs, agents, or data pipelines and you're curious about what those tools look like when applied to hard physical-world problems, this role was designed for you.
Key Responsibilities:
- Design and build LLM-powered agents that automate and augment business workflows, ranging from document handling and stakeholder communication to operational Q&A and data retrieval
- Develop conversational interfaces over structured and unstructured data, enabling non-technical users to query operational and business data in plain English
- Integrate external data sources (commodity markets, regulatory filings, industry benchmarks) into internal tools and reporting workflows
- Collaborate with SMEs (engineers, metallurgists, and project managers) to translate domain knowledge into agent behavior, prompts, and retrieval pipelines
- Contribute to a shared Python codebase, including object-oriented modules for process modeling and data transformation
- Participate in sprint reviews and stakeholder demos, iterating rapidly based on feedback from end users
Knowledge, Skills &Abilities:
Minimum Requirements:
- Currently enrolled in a BS (junior or senior standing) or MS program in Computer Science, Data Science, Software Engineering, Applied Mathematics, or a related field
- Demonstrated experience shipping an AI/ML product or tool — portfolio, GitHub, or prior internship evidence required
- Proficiency in Python, including working with APIs, data structures, and third-party libraries
- Hands-on experience with at least one LLM framework or toolchain (e.g., LangChain, LlamaIndex, OpenAI/Anthropic APIs, Haystack)
- Comfort working with structured data (SQL or Pandas) and unstructured data (PDFs, text corpora)
- Strong written communication: you'll be writing prompts, specs, and documentation alongside code
Nice to Have:
- Currently working on a PhD in Computer Science, AI, Data Science, Software Engineering, or similar
- Experience with retrieval-augmented generation (RAG), vector databases (Pinecone, Weaviate, ChromaDB), or embedding pipelines
- Familiarity with industrial, scientific, or time-series data (SCADA, historians, lab reports, assay data)
- Background or coursework in a physical science or engineering discipline (e.g. mining, metallurgy, chemical engineering, geology, or similar)
- Experience building multi-step or tool-using agents
- Exposure to BI tools or data visualization (PowerBI, Streamlit)
- Prior internship or project work in an industrial, energy, or materials company
Physical Demands
The work environment will be a mix of a typical office environment, a manufacturing floor and a construction site. Noise level: Normal office, manufacturing and construction noises.
The physical demands described here are representative of those that must be met by an employee to successfully perform the essential functions of this job. Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
The above statements are intended to describe the general nature and level of work being performed by people assigned to this job. They are not intended to be an exhaustive list of all responsibilities, duties, skills required of personnel so classified. The reporting relationship may not reflect the most recent changes to the corporate
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