Data Scientist III

Posted 2 Days Ago
Santa Clara, CA
152K-209K Annually
Senior level
Semiconductor
The Role
The Data Scientist III will develop and implement advanced AI/ML algorithms for semiconductor equipment and process development. Responsibilities include collaborating with engineers to understand process needs, creating usable code following best practices, and driving product capabilities through statistical methodologies and machine learning frameworks.
Summary Generated by Built In

Who We Are

Applied Materials is the 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 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 work beyond the cutting-edge, continuously pushing the boundaries of science and engineering to make possible the next generations of technology, join us to Make Possible a Better Future.

Our group develops AI/ML capabilities and software used daily by Applied and customer engineers for accelerating and optimizing process development on Applied tools. We are looking for a Data Scientist with experience AI/ML algorithm development to join our group and be a critical part of scaling the user base and capabilities of our software and its value to our business.

Key Responsibilities

  • Research, develop, and adopt advanced analytical, statistical, and machine learning methodologies to solve semiconductor equipment and process development problems.

  • Work with process engineers to understand and define process development problems and develop data science solutions

  • Develop new machine learning algorithms by extending existing common code base.

  • Develop code usable by others following best known coding standards and design patterns.

  • Implement modular, scalable, efficient, and robust algorithms that can be integrated into software products. Troubleshoot, debug, and improve as needed.

  • Be a team player, a part of a the strong engineering culture emphasizing collaboration and communication, and focus on objectives.

  • Collaborate with stakeholders to identify opportunities for algorithms, define deliverables, and drive towards new productized capabilities. 

Qualifications

  • M.S. or Ph.D. in one of the core engineering field, physics, chemistry, mathematics, statistics, or computer science

  • Experience of 6+ years with a Master's or 4+ years of with a PhD in data analysis and machine learning algorithm development in solving complex engineering problems

  • Experience in implementing advanced machine learning algorithms for regression, feature detection, optimization, and classification problems.

  • Solid background in mathematics (linear algebra, statistics, calculus), sequential modelling, deep learning, and Bayesian techniques

  • Experience with utilizing HPC and MLOps

  • Strong analytical and problem-solving skills, with demonstrated examples of execution from concept and feasibility to product deployment.

  • Proficiency in Python programming, solid foundation in data structures, code design patterns and algorithms.

  • Solid knowledge in machine learning frameworks (PyTorch, TensorFlow, SciPy, NumPy, Pandas, etc.)

  • Interface closely with cross-functional team (marketing, engineering, software) to define requirements, gather domain knowledge, and write software specifications

  • Excellent communication skills to crisply communicate technical content and results to cross functional teams and stakeholders.

  • Ability to drive towards general R&D direction while delivering specific use case driven capabilities under deadlines.

  • Ability to work independently with minimal direction, excellent teamwork and customer focus.

What We Offer

At Applied, we prioritize the well-being of you and your family.  Your happiness, health, and resiliency are at the core of our benefits and wellness programs.  Our robust total rewards package makes it easier to take care of your whole self and your whole family.  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.

Qualifications

Education:

Bachelor's Degree

Skills:

Certifications:

Languages:

Years of Experience:

4 - 7 Years

Work Experience:

Additional Information

Time Type:

Full time

Employee Type:

New College Grad

Travel:

No

Relocation Eligible:

Yes

U.S. Salary Range:

$152,000.00 - $209,000.00

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 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. 

Top Skills

Python
The Company
HQ: Santa Clara, CA
23,282 Employees
On-site Workplace
Year Founded: 1969

What We Do

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 enables customers to transform possibilities into reality. At Applied Materials, our innovations make possible a better future.

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