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Who We Are
Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips - the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world - like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.
What We Offer
Salary:
$161,000.00 - $221,000.00
Location:
Santa Clara,CA
You'll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible-while learning every day in a supportive leading global company. Visit our Careers website to learn more.
At Applied Materials, we care about the health and wellbeing of our employees. We're committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.
Applied Materials is the leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. Our expertise in modifying materials at atomic levels and on an industrial scale helps our customers - who make smartphones, supercomputers, virtual reality headsets, autonomous vehicles and more - transform their ideas into reality.
Inside our company, we apply the idea of making it possible as we work together. We value our people and teams who turn possibilities into reality by advancing our strategy, accomplishing great things, and empowering others. We are deeply committed to fostering a Culture of Inclusion where every person knows they belong, feels empowered to bring their whole self to work, and is inspired to grow.
Position Overview
We are seeking an AI Algorithm Developer to design and implement machine learning algorithms for semiconductor manufacturing process optimization. This role requires a strong foundation in computer science fundamentals, software engineering best practices, and deep learning/optimization algorithms. You will work on challenging problems involving sparse, noisy, high-dimensional data from semiconductor equipment, building models that predict on-wafer performance from recipe parameters.
The ideal candidate combines algorithmic depth (can reason through "why", not just implement), clean code practices (design patterns, testing, maintainable systems), and critical thinking (customizes algorithms to problem constraints rather than applying cookbook solutions).
Key Responsibilities
Algorithm Development

• Design and implement deep learning models for semiconductor process optimization (recipe inputs → metrology outputs)
• Develop Bayesian optimization strategies for sample-efficient experimental design with expensive experiments

Software Engineering

• Write clean, maintainable, scalable code following software engineering best practices
• Apply design patterns to algorithm implementations
• Develop comprehensive unit tests and validation frameworks for algorithms
• Refactor prototype algorithms into production-quality code integrated with AppliedPRO architecture
• Conduct and participate in code reviews, fostering team code quality standards
• Document design decisions, trade-offs, and algorithmic approaches clearly
• Build surrogate models and active learning frameworks for sparse, noisy manufacturing data
• Create novel algorithms that combine data-driven approaches with domain constraints
• Implement algorithms with proper data structures, computational complexity awareness, and performance optimization

Problem Solving & Innovation

• Translate semiconductor manufacturing challenges into well-defined ML problems
• Reason through trade-offs between accuracy, speed, and maintainability
• Customize algorithms to handle sparse data, noisy measurements, and expensive experiments
• Debug systematically when algorithms underperform (not trial-and-error)
• Propose and implement innovative solutions to complex optimization problems

Collaboration

• Work with domain experts to understand semiconductor process constraints
• Communicate complex algorithmic concepts to non-technical stakeholders
• Collaborate with team members on algorithm design and code architecture
• Contribute to team knowledge sharing on ML techniques and software best practices

Key Requirements

• Computer Science Foundation: Strong understanding of algorithms, data structures, computational complexity
• Software Engineering: Clean code practices, design patterns, unit testing, modular architecture
• Programming: Expert-level Python
• Deep Learning: Neural network architectures, training dynamics, optimization techniques (can explain "why", not just use libraries)
• Optimization Algorithms: Experience with gradient-based methods, Bayesian optimization, or evolutionary strategies
• Critical Thinking: Ability to reason through algorithmic choices, customize for problem constraints, debug systematically

Education & Experience

• MS or PhD in Computer Science, Applied Mathematics, Electrical Engineering, or related field
• Computer Science degree strongly preferred
• Relevant coursework: Algorithms, Machine Learning, Optimization, Software Engineering

Preferred:

• GPU programming (CUDA, performance optimization)
• Parallel computing (MPI, OpenMP, distributed training)
• Bayesian methods (Gaussian processes, uncertainty quantification)
• Active learning and sample-efficient optimization
• Software Engineering
• Experience refactoring legacy code or working with large codebases
• CI/CD, testing frameworks (pytest, unittest, integration testing)
• Design patterns in practice (Factory, Observer, Strategy, etc.)
• Version control best practices (Git workflows, code reviews)
• Performance profiling and optimization
• Domain & Research
• Publications in ML conferences/journals
• Understanding of semiconductor manufacturing or materials science
• Experience with experimental design
• Knowledge of statistical inference from noisy experimental data
• Experience with sparse, noisy, high-dimensional data
• PyTorch/TensorFlow internals knowledge

Additional Information
Time Type:
Full time
Employee Type:
New College Grad
Travel:
Yes, 10% of the Time
Relocation Eligible:
No
The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.
For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.
Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.
In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.