Data Scientist 6

## The group you\u2019ll be a part of\n\nThe Enterprise AI team within Office of CTO 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\u2019s digital transformation.\n\nWe are seeking a highly skilled and versatile Data Science / AI / ML Lead to lead the development of advanced AI/ML solutions, including but not limited to statistical modeling, computer vision, LLM/RAG workflows, optimization, and domain-specific modeling. This role works closely with product managers, forward deployed engineers, data engineers and AI/ML development engineers, translating high priority business challenges into robust, secure and explainable AI solutions aligned to business needs.\n\nThe ideal candidate combines deep technical expertise with strong stakeholder engagement skills, enabling them to act as a technical advisor, evangelist, and multiplier for AI capabilities across Lam.\n\nThe 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.\n\n## What you\u2019ll do\n\nAI/ML Technical Leadership\n\n * Develop, evaluate, and deploy state\u2011of\u2011the\u2011art ML/AI models including traditional ML, deep learning, computer vision, time-series forecasting, and LLM\u2011based systems.\n * Develop and maintain enterprise-grade ontologies that model the complex domain of semiconductor engineering.\n * Guide the use of OOTB foundation models and platforms, while leading development of custom solutions when needed (e.g., vision models, domain\u2011specific fine\u2011tuning).\n * Evaluate and integrate emerging AI technologies, frameworks, and tools aligned with business requirements and value-driven mindset.\n\n\n\nTechnical Execution \u0026 Modeling Excellence\n\n * Perform advanced data analysis using statistical and scientific methods; build proof\u2011of\u2011concept models that scale to production deployments. Mine and analyze large-scale datasets to drive operational insights, optimization opportunities, and KPI improvements.\n * Work with domain experts and ML engineers to develop feature stores, automated pipelines, and efficient MLOps workflows to speed up experimentation \u0026 model serving\n * Design and integrate ontology aware retrieval and reasoning (e.g., schema\u2011aware RAG, graph\u2011augmented retrieval, controlled vocabularies for prompts and tools) that grounds AI/ML systems (including LLMs, RAG pipelines, agents, and traditional ML) in consistent, machine\u2011interpretable business meaning.\n * Establish measurable success criteria for ontology effectiveness (e.g., reduced ambiguity, improved retrieval accuracy, explainability, reuse across use cases)\n\n\n\nCross-functional Collaboration\n\n * Work with platform teams to deploy scalable models using cloud infrastructure (e.g., Databricks, Azure ML, Azure foundry, feature stores, model registries).\n * Collaborate with software engineering teams to integrate models into applications and product workflows.\n * Support internal communities of practice; mentor data scientists and engineers to propagate best practices.\n * Act as a trusted technical advisor to business units on AI best practices, solution patterns, and technology selection.\n * Develop and deliver training, demos, and internal enablement resources to uplift AI proficiency across Lam.\n\n\n\n## Who we\u2019re looking for\n\n * Minimum of 15 years of related experience with a Bachelor\u2019s degree; or 12 years and a Master\u2019s degree; or a PhD with 8 years experience; or equivalent experience.\n * Strong in presenting data and analysis in a visually intuitive way to a broad set of stakeholders (technical and non-technical) \n * Demonstrated breadth of understanding applicability of various ML/DL methods to various domains (e.g. time-series, vision etc.) \n * 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.\n * Demonstrated expertise with Transformer architectures \u2014 including attention mechanisms, encoder\u2013decoder designs, and fine\u2011tuning foundational models for NLP, CV, or multi\u2011modal tasks.\n * Hands\u2011on experience building and optimizing Transformer\u2011based systems, including RAG pipelines, embedding models, vector databases, and efficient inference techniques.\n * Deep expertise in ontology design, semantic modeling, knowledge graphs, or domain-driven data models.\n * Hands-on experience with semantic modeling standards and techniques (e.g., ontology schemas, taxonomies, semantic constraints) and their practical application in enterprise AI systems.\n * Strong programming experience in python with demonstrated experience in package development (or open-source projects, hackathons etc.)\n * Strong in data/feature engineering with Pandas/PySpark etc. \n\n\n\n## Our commitment\n\n \n\nWe 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.\n\nLam 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\u0027s intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.\n\nLam 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 \u2013 On-site Flex and Virtual Flex. \u2018On-site Flex\u2019 you\u2019ll 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. \u2018Virtual Flex\u2019 you\u2019ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.\n\nSalary\n\nCA San Francisco Bay Area Salary Range for this position: $166,000.00 - $350,000.00.\n\nThe 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.\n\nOur Perks and Benefits \n\n\nAt Lam, our people make amazing things possible. That\u2019s why we invest in you throughout the phases of your life with a comprehensive set of outstanding benefits.\n