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. Our innovations Make Possible® a Better Future.

Inside our company, we apply the idea of make 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.

TEAM OVERVIEW:

We are passionate about creating cutting-edge, product-centric algorithmic solutions that drive innovation and deliver exceptional value to our customers. Our collaborative environment encourages out-of-the-box thinking, making us not only a powerhouse of technical expertise but also a fun and engaging team to work with. We believe that the best ideas come from diverse perspectives, and we encourage everyone to share their unique insights. This collaborative spirit fosters an environment where creativity flourishes, and groundbreaking solutions are born.

This is a highly cross functional product team which uses state-of-the-art AI/ML techniques to accelerate the pace of semiconductor application development.

An ideal candidate has demonstrated a strong research background and technical leadership in developing algorithms and softwares. The position requires a willingness to learn new technologies, solve complex problems and drive innovative solutions.

Join us on our journey to make possible a better future with AI!

KEY RESPONSIBILITIES:

• Utilize and create advanced AI and machine learning algorithms, including one-shot/few-shot learning, supervised/unsupervised learning, deep learning, and reinforcement learning, to address complex problems across various data modalities
• Design, prototype, validate, and implement high-quality, scalable algorithms with a strong focus on performance and accuracy.
• Implement algorithm designs using Python, TensorFlow, PyTorch, and C/C++, leveraging common machine learning and deep learning libraries and frameworks.
• Exhibit strong attention to detail, analytical thinking, and problem-solving abilities, ensuring robust and effective solutions.
• Thrive in a dynamic, startup-like setting, contributing to high-visibility initiatives and adapting to evolving challenges. Act as a resource for colleagues, fostering a collaborative and supportive team environment.
• Collaborate with MLOPs, software engineers and product managers to productize and optimize algorithmic pipelines, integrating them seamlessly into our software solutions

TECHNICAL SKILLS:

• Proficiency in advance AI and Machine Learning algorithms and its fundamentals
• Research experience in state-of-the-art techniques in Machine Learning, Deep Learning, Computer Vision and Generative AI
• Knowledge of frameworks such as PyTorch, TensorFlow or Keras
• Knowledge of industry best practices and competitive landscape
• Strong written and verbal presentation skills, both technical and non-technical audiences

REQUIREMENTS/EDUCATION:

• MS or Ph.D. degree in Computer Science, Computer Engineer, Electrical Engineer, Mathematics, Statistics or related field

Qualifications

Education:

Bachelor's Degree

Skills:

Certifications:

Languages:

Years of Experience:

2 - 4 Years

Work Experience:

Additional Information

Time Type:

Full time

Employee Type:

Assignee / Regular

Travel:

Yes, 10% of the Time

Relocation Eligible:

Yes

Applied Materials is an Equal Opportunity Employer committed to diversity in the workplace. All 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.