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AI Solutions lead

$141k - $307k

Lam Research

The group you'll be a part of

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.

The impact you'll make

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.

What you'll do

  • 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.
Who we're looking for
  • 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., LangChain, LangGraph) 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 pipelines, embedding models, vector databases, and efficient inference techniques.
  • Demonstrated ability to act as a single technical authority - leading design reviews, resolving cross-team architectural trade-offs, and influencing without direct authority.
  • Strong grasp of security, governance, and compliance considerations for AI systems operating on enterprise and R&D data.
  • Experience with knowledge/ontology services, semantic layers, and enterprise data foundations.
Preferred qualifications
  • Experience developing AI solutions on cloud platforms such as Azure and/or Databricks.
  • Familiarity with full-stack software or data science development
  • Strong communication skills, able to convey decisions to both technical and business audiences.

Our commitment

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.

Salary

CA San Francisco Bay Area Salary Range for this position: $141,000.00 - $307,000.00.

The above salary range for this position is relevant to applicants that reside or work onsite in the California, San Francisco Bay Area only. Salary offers will depend on factors that include the location you work from, your level, education, training, specific skills, years of experience and comparison to other employees already in this role. Actual salary may vary from salary offered due to numerous factors including but not limited to unpaid time off, unpaid leave, company mandated shutdown, and other relevant factors.

Our Perks and Benefits

At Lam, our people make amazing things possible. That's why we invest in you throughout the phases of your life with a comprehensive set of outstanding benefits.
Vacancy posted 3 hours ago
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