AI Solutions lead

In your career, let’s prove what’s possible.

At Lam Research, we create equipment that drives technological advancements in the semiconductor industry. Our innovative solutions enable chipmakers to power progress in nearly all aspects of modern life, and it takes each member of our team to make it possible.

Across our organization, our employees come to work and change the world. We take on the toughest challenges with precision and accuracy. We push for the next big semiconductor breakthrough. We lead the way in one of the most critical and fast-moving industries on the planet. And we do it together, with deep connections and limitless collaboration.

The impact we have on the world is made possible by focusing on our people. So we recognize and celebrate our teams’ achievements. We strive to create an inclusive and diverse culture where everyone’s contribution and voice has value. We evaluate and evolve our offerings, so our people receive the support and empowerment to do meaningful things for their lives, careers, and communities.

Because at Lam, we believe that when people are the priority and they’re inspired to unleash the power of innovation for a better world together, anything is possible.

Date:
Jul 14, 2026

Location:

Fremont, CA, US, 94538

Worker Category:
On-site Flex

The Office of the CTO is where innovation takes center stage. We inspire our global technical community to take on grand challenges, understand emerging trends, identify the critical inflections, and drive our sustainability, Environment, Social, and Governance (ESG) practices that will define the next generation of semiconductors and continued impact.

Join Lam as a Data Scientist, where you'll design, develop, and program methods to analyze unstructured and diverse big data into actionable insights. You'll develop algorithms and automated processes to evaluate large data sets from disparate sources. Your expertise in generating, interpreting, and communicating actionable insights enables Lam to make informed and data-driven decisions.

• Design end-to-end AI solutions on Lam's shared AI platform — AI Foundry, Agent Runtime & Orchestration, Knowledge Service, and Ontology — grounded in enterprise data.
• Translate business problems into reusable solution patterns that delivery teams can adopt across R&D and enterprise use cases.
• Serve as the technical bridge between Platforms & Technology and the AI Delivery Execution and AI Product Management teams, ensuring platform capabilities are applied consistently.
• Lead solution and design reviews, and define and enforce architectural standards for agentic, RAG, and orchestration-based solutions.
• Embed security, governance, compliance, and cost-efficiency into solution designs by default, reducing IP and data-access risk across the enterprise.
• Champion reuse of common platform primitives over duplicated point solutions, driving interoperability and lowering total cost of ownership.
• Partner with product managers, AI governance, and engineering teams to take solutions from architecture through production deployment.

• Bachelor's or Master's in Computer Science, Engineering, or a related field, with 10+ years of AI engineering experience, including significant time as a hands‑on solution or enterprise architect.
• Proven experience architecting enterprise‑scale AI/GenAI solutions — including agentic frameworks, retrieval‑augmented generation (RAG), and orchestration — as reusable, interoperable patterns.
• Deep knowledge of GenAI orchestration frameworks (e.g., Lang Chain, Lang Graph) and agent communication standards (e.g., MCP).
• Solid understanding of various ML and DL frameworks and In‑depth understanding of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real‑world advantages/drawbacks
• Demonstrated expertise with Transformer architectures — including attention mechanisms, encoder‑decoder designs, and fine ‑ tuning foundational models for NLP, CV, or multi ‑ modal tasks.
• Hands ‑ on experience building and optimizing Transformer‑based systems, including RAG…