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# Machine Learning Engineer - Generative AI

- **Company:** Applied Materials
- **Location:** Santa Clara, CA, United States (Remote available)
- **Salary:** $131,000.0 - $180,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Intelligence, Hardware Design, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Pytorch, Large Language Models, Deep Learning, Model Validation, Generative AI, Information Technology
- **Published:** August 31, 2026
- **Apply:** https://www.careerboard.com/us/en/find-jobs-in-United-States/-BA8C05071A121D20AC/

## About the Role

* 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 (eg, RLHF), and rigorous model evaluation.
 * Proficiency in Python and frameworks such as PyTorch or TensorFlow.
 * Experience working with structured and unstructured scientific data (eg, 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 Engineer, Electrical Engineer, Mathematics, Statistics or related field

## Description

* 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.


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