Data Scientist - Agentic AI / ML

Applied Materials, Inc.; Santa Clara (CA); On-site; USD 170,000 - 234,000; Full time

Job summary

Applied Materials, Inc. is seeking a senior ML engineer to drive GenAI initiatives and deploy AI‑driven solutions in semiconductor analytics. You will build analytical models, work on embedding‑based search, and guide GenAI architectures with cross‑functional teams.

Location is Santa Clara, CA on‑site. The role demands 3–5 years in applied ML, an advanced degree, and strong Python/ML framework skills; stock option eligibility and comprehensive benefits are offered.

Qualifications

• Advanced degree in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
• 3–5 years of industry experience in applied machine learning or related AI work.
• Hands‑on experience building GenAI‑focused applications (e.g., agents, reasoning workflows, or RAG) and a solid understanding of how large language models are architected and operated.
• Can work collaboratively with cross‑functional teams.
• Hands‑on experience with: Building GenAI‑focused application and applying LLMs and agentic AI (e.g., agents, reasoning workflows, or RAG) Have personally implemented models in deep learning frameworks such as PyTorch, Jax or TensorFlow.
• MLOps, including model deployment, versioning and performance monitoring in production environments.
• Proficiency in Python, SQL, and tools such as scikit‑learn, and forecasting libraries.
• Excellent analytical and problem‑solving abilities, Machine Learning Concepts.
• Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders.
• Interpersonal Skills Communicates difficult concepts and negotiates with others to adopt a different point of view.

Responsibilities

• Works in project teams developing difficult analytical models, algorithms and automated processes, research and develop machine learning models from inception to deployment.
• Work on GenAI and LLM projects, including fine‑tuning models, creating embedding‑based search systems, and developing AI‑driven prototypes to enhance business operations.
• Directing architects to design and solution GenAI architectures for stakeholders, specifically for plugin‑based solutions and custom GenAI application builds.
• Use data mining and machine learning algorithms to provide insights into historical and real‑time data for projects such as material forecast, demand forecast, pattern recognition, etc.
• Interfaces with stakeholders for requirements analysis and special requests and schedules; derives insights and works with business units to determine actions and KPI for those actions.
• Identify opportunities for forecast accuracy improvement and provide business insights and additional perspectives to Service Supply Chain leadership.
• Collaborate with Material Planning, Field Operations, Inventory Management, NPI, Production Demand Planning, Reliability Engineering, Service Campaigns Teams to gather data and bring information on key business drivers that impact the future demand on Service Parts and Accessories Requirements.

Skills

Analytical thinking

Problem-solving

Communication

Storytelling

Interpersonal skills

Education

MS or PhD in quantitative field

Tools

PyTorch

Jax

TensorFlow

scikit-learn

Forecasting libraries

Python

SQL

Job description

Who We Are Applied Materials is the global leader in materials science and engineering solutions that are at the foundation of virtually every new semiconductor chip and advanced display in the world. The equipment that we create and service is essential to advancing AI and accelerating the commercialization of next-generation semiconductor chips. Join us and push the boundaries of materials science and engineering in a company at the foundation of the electronics industry. The work we do together advances the world’s technology.

What We Offer
Salary: $170,000.00 - $234,000.00
Location: Santa Clara,CA
You’ll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible—while learning every day in a supportive leading global company. Visit our Careers website to learn more. At Applied Materials, we care about the health and wellbeing of our employees. We’re committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.

Key Responsibilities

• Works in project teams developing difficult analytical models, algorithms and automated processes, research and develop machine learning models from inception to deployment.
• Work on GenAI and LLM projects, including fine‑tuning models, creating embedding‑based search systems, and developing AI‑driven prototypes to enhance business operations.
• Directing architects to design and solution GenAI architectures for stakeholders, specifically for plugin‑based solutions and custom GenAI application builds.
• Use data mining and machine learning algorithms to provide insights into historical and real‑time data for projects such as material forecast, demand forecast, pattern recognition, etc.
• Interfaces with stakeholders for requirements analysis and special requests and schedules; derives insights and works with business units to determine actions and KPI for those actions.
• Identify opportunities for forecast accuracy improvement and provide business insights and additional perspectives to Service Supply Chain leadership.
• Collaborate with Material Planning, Field Operations, Inventory Management, NPI, Production Demand Planning, Reliability Engineering, Service Campaigns Teams to gather data and bring information on key business drivers that impact the future demand on Service Parts and Accessories Requirements.

Qualifications

• Advanced degree (MS or PhD) in a quantitative field (e.g., Statistics, Computer Science, Economics, Operations Research).
• 3-5 years of industry experience in applied machine learning or related AI work.
• Hands‑on experience building GenAI‑focused applications (e.g., agents, reasoning workflows, or RAG) and a solid understanding of how large language models are architected and operated.
• Can work collaboratively with cross‑functional teams.
• Hands‑on experience with: Building GenAI‑focused application and applying LLMs and agentic AI (e.g., agents, reasoning workflows, or RAG) Have personally implemented models in common Deep Learning frameworks such as PyTorch, Jax or TensorFlow.
• MLOps, including model deployment, versioning and performance monitoring in production environments.
• Proficiency in Python, SQL, and tools such as scikit‑learn, and forecasting libraries.
• Excellent analytical and problem‑solving abilities, Machine Learning Concepts.
• Strong communication and storytelling skills - able to simplify complexity and influence executive stakeholders.
• Interpersonal Skills Communicates difficult concepts and negotiates with others to adopt a different point of view.

Location

Santa Clara, CA; on‑site full‑time

Additional Information

Time Type: Full time Employee Type: Assignee / Regular Travel: Yes, 10% of the Time Relocation Eligible: Yes

The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable. For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.

Equal Opportunity

Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law. In addition, Applied endeavors to make our careers site accessible to all users.