Algorithm Developer II (E2) New College Graduate

at  Applied Materials

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.

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 degree in Computer Science, Computer Engineer, Electrical Engineer, Mathematics, Statistics or related field
  Qualifications

EDUCATION:

Master’s Degree

YEARS OF EXPERIENCE:

1 - 2 Years

WORK EXPERIENCE:

Additional Information

• 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