Senior AI/ML Algorithm Developer

Applied Materials, Inc.; Santa Clara, Northern (CA, KY); Hybrid; USD 161,000 - 221,000; Full time

Benefits offered by this job

Bonus potential

Stock award program

Comprehensive benefits

Job summary

Applied Materials, Inc. is seeking an Algorithm Developer III in Santa Clara, CA to drive AI/ML solutions at the intersection of physics, systems engineering, and manufacturing.

You will develop data pipelines, model physical relationships, and build predictive control algorithms for semiconductor manufacturing. You will contribute to scalable software that interfaces with real-world tools, collaborate across disciplines, and work in a fast-paced environment advancing next‑gen materials science

Qualifications

• Ph.D. in Physics, Applied Mathematics, Computational Chemistry, Electrical Engineering, Mechanical Engineering or related; or Master’s with 2+ years’ experience.
• Experience with computational methods, CAE, physics-based modeling, and complex systems.
• Experience applying ML to scientific, engineering, or industrial problems.

Responsibilities

• Design and develop scalable data pipelines for high-volume sensor data.
• Model physical relationships governing process behavior.
• Develop predictive and control algorithms combining physics and ML.
• Build maintainable software modules for real-world tools.
• Collaborate with physics, engineering, software, and data teams.

Skills

Theoretical physics

Applied mathematics

Computational science

Machine learning

Software engineering

Python

C++

Education

PhD in Physics

Master’s in Physics (2+ years exp)

Tools

GitHub

Job description

Applied Materials, Inc. is seeking an Algorithm Developer III in Santa Clara, CA to drive AI/ML solutions at the intersection of physics, systems engineering, and manufacturing.

You will develop data pipelines, model physical relationships, and build predictive control algorithms for semiconductor manufacturing. You will contribute to scalable software that interfaces with real-world tools, collaborate across disciplines, and work in a fast-paced environment advancing next‑gen materials science