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Applied Materials

Algorithm Developer

  • Office
  • 3-6 years

Salary

$184,000/ year

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Description

The company leads globally in materials science and engineering. Its equipment is used to make nearly every new semiconductor chip and advanced display, and it supports the development of AI and next-generation chips.

The team works on the foundation of the electronics industry and pushes the limits of materials science and engineering in a supportive environment where people keep learning.

Responsibilities

  • You will lead research, design, development and implementation of algorithm modules.
  • You will assess the feasibility of image processing algorithms, covering problem analysis, data collection, literature review, choosing and evaluating concepts, and implementation limits.
  • You will build and evaluate computer vision and machine learning or deep learning algorithms for defect detection, defect classification, metrology and image analysis.
  • You will prototype new algorithmic approaches for hard problems after studying customer use cases closely.
  • You will work with software, systems and applications teams to turn algorithm solutions into products that meet defined specifications.
  • You will optimize algorithms to lower computational cost and reduce hardware demands.

Requirements

  • You have proven experience in the semiconductor industry.
  • You have a strong background in computer vision, image processing and deep learning.
  • You are proficient in C/C++ and Python and have hands-on experience with frameworks such as TensorFlow, PyTorch or similar.
  • You have a solid academic foundation in computer vision, deep learning, machine learning or artificial intelligence.
  • You have excellent analytical, problem-solving and organizational skills, along with strong interpersonal and communication abilities.
  • You hold a Ph.D. in computer science, electrical engineering or a related field with 4+ years of experience, or a Master's degree with 7+ years of experience.
  • Optional: GPU programming such as CUDA and algorithm optimization and tuning skills are desired.
  • Optional: working knowledge of AI-assisted coding tools is a plus.

Conditions

Full-time, regular assignee role based in Santa Clara, CA.

Salary ranges from $184,000.00 to $253,000.00.

Pay depends on location, hire grade, job knowledge, skills, experience and internal equity with current team members.

Candidates may also be eligible for a bonus and a stock award program, where applicable.

For sales roles, the posted range is the Target Total Cash range, meaning base salary plus target bonus at 100% goal achievement.

Travel is required 10% of the time.

Relocation assistance is available.

Benefits

  • A comprehensive benefits package with wellness programs that support your happiness, health and resilience, plus total rewards that cover you and your family.
  • Programs that support personal and professional growth, and care for you at work, at home and beyond.
  • A work culture that encourages you to learn, develop your career and take on challenges to drive new solutions for customers.

Where you’d work

From the office

About the company

Applied Materials

Office in United States

Also hiring in Austin, United States, Phoenix, United States, Eindhoven, Netherlands and 15 more places

2 of their 174 open roles are remote

Your chances

Worth a look before you spend an evening tailoring a CV for it.

  • 21 checks run
  • 1 red flag

Still hiring?

14 checks

1 red flag

How crowded?

7 checks

No red flags

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  • Must-haves
Details11 facts · Role, Location, Compensation, Employment
Tech stack
  • Python
  • PyTorch
  • C++
  • CUDA
Type
Full-time
Equity
Equity offered
Specialty
ML
Region
United States
Pay period
Annual
Show 5 more factsShow less

Role

Category
Data & Analytics
Specialty
ML
Experience
4+ years
Tech stack
  • Python
  • PyTorch
  • C++
  • CUDA

Location

Work model
Office
Region
United States
Office
  • United States

Compensation

Salary
$184,000 / year
Pay period
Annual
Equity
Equity offered

Employment

Type
Full-time

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