Data Science AI/ML Lead

The group you’ll be a part of

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.  

The impact you’ll make

We 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. The 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. This role works closely with subject matter experts, data engineers, ML engineers, and product managers to ensure AI solutions are robust, explainable, and aligned to business needs. 

What you’ll do

Key Responsibilities 

AI Solution Leadership 

• Develop, evaluate, and deploy state of the art ML/AI models including traditional ML, deep learning, computer vision, time-series forecasting, and LLM based systems (RAG vs. fine-tuning decision-making). 
• Guide the use of OOTB foundation models and platforms, while leading development of custom solutions when needed (e.g., vision models, domain specific fine-tuning). 
• Partner with business stakeholders and SMEs to identify high value opportunities and craft wellformed data science problem statements with strong ROI potential. 

Technical Execution & Modeling Excellence

• Perform advanced data analysis using statistical and scientific methods; build proof of concept models that scale to production deployments. 
• Mine and analyze large-scale data sets to drive operational insights, optimization opportunities, and KPI improvements. 
• Work with domain experts and ML engineers to develop feature stores, automated pipelines, and efficient MLOps workflows to speed up experimentation & model serving  

Cross-functional Collaboration

• Work with platform teams to deploy scalable models using cloud infrastructure (e.g., Databricks, Azure ML, Azure foundry, feature stores, model registries). 
• Collaborate with software engineering teams to integrate models into applications and product workflows.
• Support internal communities of practice; mentor data scientists and engineers to propagate best practices.
• Act as an advisor to business units on AI best practices, solution patterns, and technology selection. 
• Develop and deliver training, demos, and internal enablement resources to uplift AI proficiency across Lam. 

Who we’re looking for

Skills Requirements 

• Strong in presenting data and analysis in a visually intuitive way to a broad set of stakeholders (technical and non-technical), experience with viz tools based on Python(Dash etc.) 
• Demonstrated breadth of understanding applicability of various ML/DL methods to various domains (e.g. time-series, vision etc.) 
• 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.
• Feature pipelines and/or model development experience in Vision, data augmentation/automated labeling or time-series or reinforcement learning (OpenAI gym, PyTorch, Tensorflow, Keras, scikit learn etc.), simulation/model predictive control 
• Strong programming experience in python with demonstrated experience in package development (or open-source projects, hackathons etc.), API development 
• Strong in data/feature engineering with Pandas/PySpark etc. 
• MS/PhD in engineering disciplines preferred 

Preferred qualifications

Prior experience in any of the following areas would be great! 

• Publication record in ML conferences  
• Familiarity with full-stack software or data science development
• Familiarity in working in Databricks environment 
• Familiarity with Docker, Kubernetes etc  

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.

#LI-DM1