Key Responsibilities
Research, develop, prototype, and evaluate computer vision, image analysis, signal processing, and machine learning algorithms for semiconductor wafer inspection and metrology applications.
Conduct benchmarking and validation studies to evaluate algorithm accuracy, robustness, computational efficiency, and overall performance.
Implement, optimize, and maintain product-quality algorithmic software in Python and C++ for production and deployment.
Collaborate with software, systems, applications, and compute infrastructure teams to integrate algorithms into production products.
Document technical findings and communicate results through reports, presentations, and design reviews.
Minimum Qualifications
Recent Master's or Ph.D. graduate in Electrical Engineering, Computer Science, or a related field, with specialization in Computer Vision, Image Processing, Signal Processing, Machine Learning, or related areas.
Graduate-level coursework in classical and modern computer vision, along with hands-on project work in image registration, image segmentation, camera calibration, multi-view geometry, and related image analysis techniques.
Proficient in Python and/or C++ through research, coursework, internships, or academic projects.
Preferred Qualifications
Experience applying mathematical and statistical methods to formulate and solve engineering problems.
Experience with image-based deep learning methods for computer vision applications.
Experience using AI-assisted coding tools for software development, prototyping, and debugging.
Publications in leading peer-reviewed conferences or journals (e.g., CVPR, ICCV, ECCV, ICIP, or similar venues).
Additional Skills
Familiarity with machine learning frameworks such as PyTorch, TensorFlow, or equivalent tools.
Strong analytical, problem-solving, and communication skills.
Ability to work effectively in a collaborative, cross-functional engineering environment.
Qualifications
Education: Master's Degree or Ph.D.
Years of Experience: 0-2 Years
Work Experience: New College Graduate
Additional Information
Travel: Up to 10%
Relocation Eligible: Yes
Hiring Profile Summary
This position targets high-potential Master's and Ph.D. graduates with strong foundations in computer vision, image processing, signal processing, and machine learning. The role focuses on the research, development, validation, optimization, and deployment of algorithms for semiconductor wafer inspection and metrology applications while providing opportunities to work closely with multidisciplinary engineering teams to solve challenging real-world manufacturing problems.
Additional Information
Time Type
Full time
Employee Type
New College Grad
Travel
Not Specified
Relocation Eligible
Yes
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.
