AI Research Scientist - Algorithm

About this role

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Skills you'll use

What you'll do

• Develop, pretrain, 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.

Who can apply

• 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 (SFT), post-training alignment (e.g., RLHF), and rigorous model evaluation.
• Proficiency in Python and frameworks such as PyTorch or TensorFlow.
• 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.

Perks & benefits

About Applied Materials

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