This role offers the opportunity to work on high‑impact, cross‑functional initiatives and to develop end‑to‑end AI solutions—from problem formulation to production deployment.:
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
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.
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. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.
