Data Scientist 5 at Lam Research

Bengaluru, karnataka, India -

Full Time

Start Date

Immediate

Expiry Date

20 Feb, 26

Salary

0.0

Posted On

22 Nov, 25

Experience

10 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Data Science, Machine Learning, Artificial Intelligence, Python, JavaScript, TypeScript, Frontend Frameworks, API Development, DevOps, Azure, GenAI Applications, RAG, Function-Calling, Agentic Architectures, Software Development Life Cycle, Problem-Solving, Communication Skills

Industry

Semiconductor Manufacturing

Description

Lead design and development of GenAI-based applications powered by retrieval augmented generation (RAG), text-to-SQL, function-calling, and agentic architectures. Architect and implement scalable solutions for ingesting, cracking, parsing, and indexing large-scale enterprise data for use in RAG-based systems. Establish and implement software development life cycle (SDLC) best practices, including requirement analysis, coding standards, code reviews, source control management, build processes, testing, and operations. Interact with business stakeholders to gather feedback and tailor solutions to business needs. 12+ years of experience in software engineering, machine learning, data science, or artificial intelligence. Typically requires a minimum of 12 years of related experience with a Bachelor's degree; or 8 years and a Master's degree; or a PhD with 5 years experience; or equivalent experience. 12+ years of experience in software engineering, machine learning, data science, or artificial intelligence. Proficiency in Python, JavaScript/TypeScript, and modern frontend frameworks like Svelte. Experience in full-stack software engineering with a focus on API development and frontend technologies. Experience throughout the software development life cycle, including requirements gathering, design, architecture, development, testing, deployment, maintenance, frontend, backend, and DevOps. Proficiency using Azure or similar cloud computing ecosystem, including AI services like Azure OpenAI and Azure AI Search. Strong communication skills, and ability to collaborate with cross-functional teams. Strong problem-solving skills and the ability to work in a fast-paced, dynamic environment. Experience developing GenAI applications leveraging LLMs, including chatbots using RAG, function-calling, and agentic architectures. Experience with GenAI development tools such as OpenAI, LangChain, and GraphRAG. 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 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.

Responsibilities

Lead the design and development of GenAI-based applications and architect scalable solutions for large-scale enterprise data. Interact with business stakeholders to gather feedback and tailor solutions to meet business needs.