AI Research Scientist; Generative Models Scientific Discovery

Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting‑edge equipment that helps our customers manufacture display and semiconductor chips – the brains of devices we use every day. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.

Salary: $ - $

Location:

Santa Clara, CA

You’ll benefit from a supportive work culture that encourages learning, development, and growth while taking on challenges and driving innovative solutions for our customers.

We are a passionate, cross‑functional team at the forefront of applying cutting‑edge AI and machine learning to accelerate scientific and materials innovation. Our mission is to create domain‑specific, product‑centric algorithmic solutions that drive real impact for our customers. We thrive in a collaborative environment that encourages out‑of‑the‑box thinking and values diverse perspectives.

• Develop, pre‑train, fine‑tune, and align LLMs and generative models tailored for scientific and materials science data, literature, and workflows.
• Innovate post‑training methods, alignment, and evaluation for domain‑specific LLMs, ensuring models are robust, accurate, and trustworthy for scientific use cases.
• Design and implement generative approaches to accelerate materials discovery, hypothesis generation, and hardware design.
• Collaborate with scientists, engineers, and cross‑functional teams to identify impactful applications of generative AI in materials science.
• Build and curate scientific datasets, benchmarks, and evaluation protocols for model validation and continuous improvement.
• Stay current with advances in AI, machine learning, and materials science, and publish original research in top venues.
• Mentor junior team members and contribute to a collaborative, inclusive research culture.

• Strong background in machine learning, deep learning, NLP, and generative AI, with a focus on scientific or technical domains.
• Hands‑on experience with LLM pretraining, supervised fine‑tuning, post‑training alignment (e.g., RLHF), and rigorous model evaluation.
• Proficiency in Python and frameworks such as PyTorch or Tensor Flow.
• Experience working with structured and unstructured scientific data (e.g., literature, experimental results, simulation outputs) and developing domain‑specific models.
• Excellent communication skills, with the ability to collaborate across disciplines and present complex ideas to diverse audiences.

• MS or Ph.D. degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics, Statistics, or a related field.

• Time Type:
  Full time
• Employee Type:
  Assignee / Regular
• Travel:
  No
• 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.

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.

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