Вакансия из Hirify Global, списка международных tech-компаний Для мэтча и отклика нужен Plus
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$161к-221к/год
$170к$210кмедиана$250к
По похожим ролям (49) ~ $210к/год
На СНГ рынке: $4.7к/мес ($3.9к - $6к)
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Крутая вакансия
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Чётко очерченная роль в Scientific AI сочетает прикладные исследования и инженерные задачи в крупной полупроводниковой компании, но требования к PhD и работа в офисе делают возможность довольно специализированной.
На стыке AI и науки
Современный стек
Исследования в деле
?Нужна степень PhD
Мэтч & Сопровод
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Описание вакансии
Текст:
Hirify AI/Оригинал
TL;DR
Physics AI Scientist III (Scientific AI/Semiconductors): Develop next-generation AI models for semiconductor engineering by combining physics-based simulation, scientific computing, and machine learning with an accent on surrogate models, operator learning, and foundation models. Focus on building scalable data, training, validation, and deployment workflows, collaborating with engineering experts, and advancing Scientific AI applications.
Location: Santa Clara, CA, United States of America; travel required 10% of the time; relocation eligible.
Salary: $161,000–$221,000 per year.
Company
hirify.global develops materials science and engineering solutions and equipment for semiconductor chips and advanced displays.
What you will do
Develop Scientific AI models combining scientific computing, physics-based simulation, and machine learning for physics- and chemistry-based engineering problems.
Design and train surrogate models, operator-learning models, and foundation models for scientific simulations.
Collaborate with domain experts to formulate AI solutions for complex engineering challenges.
Build scalable data generation, training, validation, and deployment workflows.
Publish technical innovations and drive adoption of Scientific AI across engineering applications.
Requirements
Ph.D. in Mechanical Engineering, Chemical Engineering, Materials Science, Physics, Applied Mathematics, Computer Science, or a related field.
Experience applying machine learning to real-world scientific or engineering problems.
Strong background in scientific machine learning and numerical simulation.
Experience with surrogate modeling, PINNs, operator learning such as FNO, or foundation models.
Proficiency in Python and PyTorch.
Experience with HPC, distributed training, large-scale scientific datasets, or scalable ML workflows.
Culture & Benefits
Full-time regular employment with a supportive work culture focused on learning, development, and career growth.
Comprehensive benefits and programs supporting employee health and wellbeing.
Additional compensation may include a bonus and stock award program, as applicable.
Travel is required 10% of the time.
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