Data Scientist 3

LAM RESEARCH Corporation; Bengaluru; Hybrid; INR 1,500,000 - 2,200,000; Full time

Benefits offered by this job

Hybrid work options

On-site/Remote flexibility

Job summary

Lam Research is seeking an experienced AI/ML engineer to design, develop, and deploy end-to-end AI/ML solutions across business needs. You will work with data scientists and engineers to build scalable architectures and production-grade models using PyTorch and modern ML techniques.

The role emphasizes MLOps, model monitoring, and governance in cloud environments (Azure, AWS, or GCP). Collaborative teamwork and agile practices are essential for rapid POC delivery and impact.

Qualifications

• 5+ years delivering enterprise-scale data science and AI/ML solutions.
• Strong Python and ML/DL frameworks experience.
• Experience with cloud platforms and MLOps practices.

Responsibilities

• Design, develop, and deploy end-to-end AI/ML and Generative AI solutions.
• Collaborate with data scientists, engineers, and stakeholders to translate problems into technical solutions.
• Lead MLOps, monitoring, and governance for production-grade models.
• Drive agile project delivery and rapid POC development.

Skills

Python

PyTorch

ML/DL frameworks

Education

Bachelor’s degree or higher in CS/Math/Engineering

Tools

Azure

Hadoop

Spark

Job description

The group you’ll be a part ofThe 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 makeIn 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 doDesign, 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 for5+ 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 qualificationsExperience designing large-scale AI/ML or GenAI architectures.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 commitmentWe 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.