Intern Grounded GenAI & Multimodal Knowledge Systems

Summary

As an intern at James Hardie you will have the opportunity to gain hands-on experience in your chosen field whether it be HR Engineering Finance Marketing IT or another function. This is a12-week paid internship programdesigned to provide you with valuable insights into the industry enhance your skills and prepare you for a successful career. You will work closely with experienced professionals contributing to real projects that impact our business. Additionally you will have access toexclusive mentoring opportunitiesto help guide your professional development.

Internship Objective:

This internship focuses on delivering a productionready prototype of a tightly grounded GenAI assemblyguidance assistant while developing realworld capability in RAG knowledge structuring evaluation and safe efficient system design using modern Azurebased AI tooling. It directly advances departmental goals by improving customer safety and clarity accelerating internal technical workflows establishing scalable knowledge governance and enabling costdisciplined deployment of AIpowered support experiences.

What Youll Do:

General Responsibilities:

• Work with team members on diverse projects and tasks.
• Perform research and analysis to aid project objectives.
• Create reports presentations and necessary documentation.
• Engage in team meetings and share ideas.
• Learn and implement industry best practices and company standards.

Engineering Responsibilities:

• Build/Evaluate a controlled RAG pipeline over product manuals and engineering docs including document ingestion chunking indexing retrieval (hybrid where applicable) and reranking.
• Implement safety/grounding controls: citations per step/claim abstain/clarify behavior when evidence is insufficient and a verification pass to detect missing evidence or conflicts.
• Develop ontology metadata schema for assembly-level reasoning (assemblies/subassemblies/parts/tools/specs/procedures/safety warnings) and apply it to improve retrieval precision and applicability filtering (model/variant/revision).
• Create an evaluation harness (golden question set rubrics regression tests dashboards) to measure groundedness refusal correctness safety and answer usefulness over time.
• Prototype a video-to-evidence workflow (internal mode): generate searchable evidence objects (transcripts timestamps segments tags) and define a governance pathway to promote vetted knowledge into canonical sources.
• Prototype an end-to-end research document ingestion pipeline for domain-expert reasoning of research literature downstream experimental insights leveraging paper-qa lab bench nemotron-parse or similar tools.

What Youll Bring:

• Must be enrolled in a bachelors program in a relevant discipline at an accredited university with an anticipated graduation date between December 2026 and May 2028 (rising junior or rising senior).
• Demonstrated strong academic performance with a minimum GPA of 3.0.
• Must be available to work full-time for 12 weeks during the summer of 2026.
• Must have reliable transportation to and from the work location.
• Must be authorized to work in the US.

Preferred Skills:

• Target major: Computer Science (AI/ML NLP/Language Tech Intelligent Systems) Data Science / Applied Data Science / Computational Data Science Artificial Intelligence (where offered) Computational Linguistics (CS/Linguistics) Information Science / Informatics / Information Studies / Information Management
• Familiarity with the following platform(s): Google Cloud MS Azure NVIDIA Nemotron AWS Bedrock
• RAG & Search: document ingestion/chunking embeddings hybrid retrieval (keyword vector) reranking and citation-grounded answer generation.
• Document understanding: parsing PDFs/HTML/tables text normalization metadata extraction deduplication and version/applicability tagging for manuals/engineering docs.
• Evaluation & verification: golden test set creation automated regression tests groundedness checks (citation coverage per step/claim) refusal/abstain gating and failure mode analysis.
• Multimodal evidence pipelines: video ASR/transcription timestamped segmentation indexing/search over segments and tagging evidence objects to ontology entities with provenance (tier review state).
• Deployment & performance: Azure-based implementation API integration with LLMs (Azure OpenAI Gemini fallback) latency/cost profiling caching/routing policies and basic on-device inference workflows (quantization awareness/ONNX a plus).

What Youll Receive:

As of the date of this posting a good faith estimate of the current pay scale for this position is $22 to $25. Placement in the range depends on several factors such as experience skills geography and may change over time.

• Full-time work experience and competitive pay
• Meaningful projects
• Mentorship and guidance
• Feedback and evaluation
• Company culture
• Networking opportunities and skill development

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