Machine Learning Engineer, Generative AI

Applied Materials

Quick summary

Work type
On-site
Location
Santa Clara, CA
Salary
$131,000–$180,000 / yr
Posted
6 days ago
Nearby
99+ roles within 25 mi

Market check

Salary context

Below market

How this pay compares to similar roles

Similar $210k
This role $156k
$116k most similar roles pay here $273k

This role pays less than 88% of similar roles. Most pay $174,311–$246,150 — the shaded band above. At the midpoint, this role pays about $156k versus about $210k for comparable roles.

Based on 240 similar postings.

Employer

About Applied Materials

Applied Materials is the world''s largest supplier of equipment, services, and software for the semiconductor and display industries, enabling the production of chips and advanced displays. Industry: Semiconductor Equipment

Applied Materials currently has 95 open roles on FindRole.

Listed pay typically runs $133,500–$183,500 across 95 roles with salary data.

Most-posted roles

View all roles at Applied Materials

At a glance

TL;DR · Machine Learning Engineer, Generative AI

Role Posting Log in to save

Join our passionate cross-functional team at the intersection of AI and materials science as a Senior Machine Learning Engineer, where you will develop and fine-tune large language models (LLMs) for scientific applications. Your day-to-day involves innovating post-training methods to ensure robust and trustworthy models, designing generative approaches to accelerate materials discovery, and collaborating with scientists and engineers to identify impactful AI-driven solutions. You will also build datasets and evaluation protocols, stay current with advancements in AI and publish research. Ideal candidates have a strong background in machine learning, deep learning, NLP, and experience with frameworks like PyTorch or TensorFlow, along with proficiency in Python. This role requires a MS or Ph.D. in Computer Science, Engineering, Mathematics, Statistics, or related field, and offers opportunities to mentor junior team members while contributing to cutting-edge research in materials science innovation.

Skills

Python PyTorch TensorFlow LLMs NLP RLHF Generative AI Machine Learning Deep Learning Scientific Datasets Benchmarks Evaluation Protocols

What you'll do

  • Develop and fine-tune LLMs for scientific and materials science applications.
  • Innovate post-training methods to ensure domain-specific models are robust and accurate.
  • Design generative approaches to accelerate materials discovery and hardware design.
  • Build and curate scientific datasets and benchmarks for model validation.
  • Stay current with AI, machine learning, and materials science advancements.
  • Publish original research in top venues related to AI and materials science.

What we're looking for

  • Strong background in machine learning, deep learning, and generative AI.
  • Experience with large language model pretraining and fine-tuning techniques.
  • Hands-on work with scientific data and development of domain-specific models.
  • Proficiency in Python and deep learning frameworks like PyTorch or TensorFlow.
  • Ability to innovate and evaluate post-training methods for LLMs.
  • MS or Ph.D. degree in a relevant technical field such as Computer Science.
  • Excellent communication skills for cross-disciplinary collaboration.

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