below marketmost similar roles pay hereabove market
This role pays more than
68%
of similar roles. Most pay
$135,000–$199,777
— the blue band above.
At the midpoint, this role pays about
$191k
versus about
$167k
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
365 open roles
on FindRole.
Listed pay typically runs
$126,000–$173,500
across 226 roles with salary data.
The Algorithm Developer III joins the Rocket team to advance rapid innovation methodologies within semiconductor manufacturing. This role operates at the intersection of artificial intelligence, theoretical physics, and systems engineering to solve complex manufacturing challenges. You will design scalable data pipelines to process high-volume sensor data, identify physics-based relationships, and build predictive and control models. Key responsibilities include developing physics-informed neural networks, ML surrogates, and reduced order models to optimize manufacturing processes in real time. You will build robust software modules that integrate with real-world tools, maintaining a clean codebase for production-ready applications. Required skills include expertise in theoretical physics, applied mathematics, or computational science, alongside proficiency in machine learning, statistical modeling, and software engineering to translate complex algorithms into functional systems for physical-world applications.
Design and develop scalable data pipelines to process high-volume sensor data from manufacturing systems.
Identify and model underlying physical relationships governing complex semiconductor process behaviors.
Develop predictive and control algorithms using a hybrid of physics-based methods and machine learning.
Build robust software modules that integrate directly with real-world manufacturing tools and systems.
Develop ML surrogates or reduced order models based on rigorous physics simulations.
Optimize accuracy and performance tradeoffs to ensure high-speed execution of algorithm modules.
Implement models and code for user-facing applications, control systems, or dashboards.
Maintain a clean and consistent code base that can be extended by the team.
What we're looking for
Ph.D. in Physics, Applied Mathematics, Computational Chemistry, Electrical Engineering, Mechanical Engineering, or a related quantitative discipline.
Master’s degree in Physics, Applied Mathematics, Computational Chemistry, Electrical Engineering, Mechanical Engineering, or a related quantitative discipline with at least 2 years of relevant industry or research experience.
Deep expertise in theoretical physics, applied mathematics, computational science, or simulation-driven engineering.
Working knowledge of modern machine learning, data science, and statistical modeling techniques.
Strong software engineering capabilities to translate complex algorithms into clean, scalable, and production-ready code.
Demonstrated ability to develop high-quality, maintainable code through public repositories, open-source contributions, or peer-reviewed publications (preferred).
Experience with computational methods, computer-aided engineering, engineering simulation, physical modeling, or complex systems analysis (preferred).
Experience applying machine learning techniques to scientific, engineering, or industrial problems (preferred).
Python
Machine Learning
Deep Learning
SQL
React
time series analysis
Data Science
Signal Processing
Statistical Data Analysis
Regression
Classification
Clustering
Hypothesis Testing
Semiconductor Process