Data Scientist, Lead
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, develop, and deploy end-to-end Machine Learning, Deep Learning, and Generative AI solutions that address complex business challenges.
*Build and maintain production-grade AI/ML systems that are reliable, scalable, and aligned with enterprise standards.
*Analyze large and complex datasets from multiple sources to develop predictive models and actionable insights.
*Develop APIs and AI-powered applications that integrate machine learning models into business workflows using the Azure technology stack.
*Collaborate with product, engineering, analytics, and business teams to translate requirements into impactful data science solutions.
*Rapidly develop proof-of-concepts (POCs), evaluate performance, and iterate solutions based on stakeholder feedback and business needs.
*Monitor and improve model performance, scalability, fairness, and operational reliability in production environments.
Stay current with emerging AI, ML, and Generative AI technologies and apply innovative approaches to real-world problems.
Who we’re looking for
*Bachelor's, Master's, or Ph.D. degree in Computer Science, Data Science, Statistics, Artificial Intelligence, or a related field.
*6+ years of experience developing and deploying enterprise-scale Data Science, Machine Learning, or AI solutions.Strong hands-on programming experience with Python and machine learning frameworks such as Scikit-learn, PyTorch, or similar libraries.
*Proven experience deploying ML/DL/GenAI models into production environments.
*Experience building APIs and integrating machine learning models into applications.Strong analytical and problem-solving skills with the ability to work on large, complex datasets.
*Experience delivering rapid prototypes and proof-of-concepts while balancing scalability and performance
Preferred qualifications
*Experience with Azure cloud services, Azure Virtual Machines, and MLOps practices.
*Hands-on experience with Large Language Models (LLMs), Retrieval Augmented Generation (RAG), prompt engineering, and agentic AI frameworks.Familiarity with model monitoring, optimization, and governance in production environments.
*Experience working in cross-functional product and engineering teams.
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.