Applied AI Intern - Summer 2026

The AI Hub within Global Information Systems (GIS) is a centralized, high impact group responsible for developing, scaling, and evangelizing AI capabilities across Lam Research. The team partners closely with product managers, engineering teams, business units to deliver AI-enabled solutions that drive measurable business value and accelerate Lam's digital transformation. We are seeking a candidate who can start in May 2026 and are available for a 12 week long internship.

In this role, you'll engage in solving complex business problems using AI/GenAI as an enabler. Your contributions will directly influence the development of Lam's AI Hub platform. This internship offers a rare opportunity to work with cutting-edge GenAI technologies at an enterprise scale. You will gain hands-on exposure to enterprise-scale GenAI orchestration, retrieval systems, and platform UI/UX.

By the end of the internship, you will have: Delivered a working prototype or platform enhancement in AI Hub, contributed to a RAG or orchestration workflow used by internal teams & documented technical findings and presented outcomes to stakeholders.

• Collaborate with the AI Hub data science team to design and implement specific components of the AI Hub platform.
• Assist in data collection, cleaning, and preprocessing tasks to improve Retrieval Augmented Generation (RAG) and function/tool calling processes in support of complex Generative AI projects.
• Run a scoped pilot to fine-tune foundation models using curated, compliant datasets, evaluate performance against defined metrics, and integrate learnings into AI Hub's platform workflows.
• Contribute to UI/UX redesign of the AI Hub platform and suggest specific UI changes to existing AI products to enhance usability and visualization of orchestration workflows.
• Document and communicate findings, insights, and recommendations to stakeholders.

• Currently enrolled MS or PhD students in Computer Science, Engineering, Statistics, or related fields, with a strong academic record.
• Strong understanding of machine learning concepts and algorithms, including deep learning, transformerbased systems, embedding models, vector databases, etc.
• Hands-on experience or academic/project exposure to GenAI orchestration frameworks (e.g., LangChain, LangGraph) and AI agent communication concepts (e.g., MCP).

• Experience fine-tuning language models such as GPT or BERT
• Experience developing in cloud platforms, like Azure and/or Databricks.
• Knowledge of distributed computing frameworks, such as Apache Spark.
• Familiarity with data engineering concepts and practices.
• Strong communication skills for effective collaboration across teams
• Ability to work independently in a dynamic, fast-paced environment

We believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.

Lam Research ("Lam" or the "Company") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.

Lam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. 'On-site Flex' you'll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. 'Virtual Flex' you'll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.