Data Scientist 3

Lam Research Salzburg GmbH; Bengaluru; Hybrid; INR 1,500,000 - 2,100,000; Full time

Job summary

Lam Research Salzburg GmbH is seeking an experienced Data Scientist to build scalable AI/ML and Generative AI capabilities. You will design modern architectures, deploy production-grade models, and push innovation across the organization.

The role emphasizes collaboration with data scientists, engineers, and business stakeholders to translate problems into measurable outcomes. The team operates in an on-site/ hybrid setting in Bangalore, with a focus on delivering fast POCs, robust governance,

Qualifications

• 5+ years delivering enterprise-scale data science and AI/ML solutions.
• Strong programming in Python or R with ML/DL frameworks.
• Experience with cloud platforms and big-data tech; ML deployment and MLOps.

Responsibilities

• Design and deploy end-to-end AI/ML and Generative AI solutions for business needs.
• Build scalable ML architectures; evaluate tools and frameworks for SciML and digital twins.
• Develop production-ready models in cloud environments with MLOps practices.
• Collaborate with data scientists, engineers, and stakeholders to translate problems into solutions.
• Lead technical design discussions and guide teams through AI/ML challenges.
• Establish monitoring and governance for model reliability and improvement.
• Deliver rapid POCs and extract insights from complex datasets.
• Work schedule aligns with standard business hours, with cross-team flexibility.

Skills

Python/R

PyTorch

ML/DL frameworks

Agile

Communication

Education

Bachelor’s/Master’s/PhD in CS/DS/Engineering/Mathematics/Physics

Tools

Azure

AWS

GCP

Hadoop

Spark

NVIDIA Modulus

PyTorch Geometric

Job description

In your career, let’s prove what’s possible.

At Lam Research, we create equipmentthat drives technological advancements in the semiconductor industry. Our innovative solutions enable chipmakers to power progress in nearly all aspects of modern life, and it takes each member of our team to make it possible.
Across our organization, our employees come to work and change the world. We take on the toughest challenges with precision and accuracy. We push for the next big semiconductor breakthrough. We lead the way in one of the most critical and fast-moving industries on the planet. And we do it together, with deep connections and limitless collaboration.
The impact we have on the world is made possible by focusing on our people. So we recognize and celebrate our teams’ achievements. We strive to create an inclusive and diverse culture where everyone’s contribution and voice has value. We evaluate and evolve our offerings, so our people receive the support and empowerment to do meaningful things for their lives, careers, and communities.
Because at Lam, we believe that when people are the priority and they’re inspired to unleash the power of innovation for a better world together, anything is possible.

Data Scientist 3

Date: Sep 28, 2026

Location: Bangalore, IN-Bangalore, IN

Worker Category: On-site Flex

The group you’ll be a part of

The Office of the CTO is where innovation takes center stage. We inspire our global technicalcommunity to take on grand challenges, understand emerging trends, identify the criticalinflections, and drive our sustainability, Environment, Social, and Governance (ESG) practicesthat will define the next generation of semiconductors and continued impact.

The impact you’ll make

In this role, you will directly contribute to building scalable AI and machine learning solutions that empower our teams to make faster, smarter decisions. You’ll help shape the next generation of AI capabilities by designing modern architectures, deploying production-grade models, and driving innovation across the organization.

What you’ll do

• Design, develop, and deploy end-to-end AI/ML and Generative AI solutions that support critical business needs.
• Build scalable machine learning architectures and evaluate modern tools, frameworks, and platforms to strengthen our data science ecosystem, including solutions for Scientific Machine Learning (SciML), surrogate modeling, digital twins, and simulation-driven AI applications.
• Develop production-ready models and deliver solutions on cloud environments (preferably Azure) using strong MLOps practices, with exposure to deep learning frameworks such as PyTorch and emerging architectures including physics-informed AI models and neural operators.
• Partner closely with data scientists, engineers, and business stakeholders to translate business problems into technical solutions with measurable impact.
• Lead technical design discussions, guide teams through complex AI/ML challenges, and foster a collaborative innovation culture.
• Establish monitoring, governance, and fail-safe mechanisms to ensure model reliability and continuous improvement.
• Deliver rapid POCs and extract meaningful insights from diverse and complex datasets.
• Work Schedule: Standard business hours with flexibility to collaborate across teams.

Who we’re looking for

• 5+ years of experience delivering enterprise-scale data science and AI/ML solutions.
• Bachelor’s, Master’s, or Ph.D. in Computer Science, Data Science, Engineering, Applied Mathematics, Physics, or a related field.
• Strong programming skills in Python or R and expertise with ML/DL frameworks, including hands-on experience with PyTorch and modern deep learning techniques.
• Experience applying machine learning techniques to scientific computing, engineering simulations, surrogate modeling, or related data-intensive problem domains.
• Experience with cloud platforms (Azure, AWS, or GCP) and big-data technologies (e.g., Hadoop, Spark).
• Proven understanding of MLOps, model deployment, and ML fail-safe principles.
• Hands-on experience in leading projects using agile methodologies.
• Strong communication and stakeholder-management skills.

Preferred qualifications

• Background in building highly scalable production ML systems.
• Familiarity with advanced statistical modeling, applied machine learning techniques, and emerging areas such as Scientific Machine Learning (SciML), Physics-Informed AI, Neural Operators, and Digital Twin technologies.
• Exposure to frameworks and methodologies such as PINNs, PINO, DeepONet, Fourier Neural Operators (FNO), MeshGraphNets, NVIDIA Modulus, PhysicsNeMo, PyTorch Geometric, PDE learning, operator learning, geometry-aware sampling, or multi-physics simulation is a strong plus.
• Experience guiding teams in high-impact technical environments.
• Understanding of engineering simulation workflows, scientific computing, or physical systems modeling is desirable.

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.