Research Scientist - Computer Vision and Deep Learning
Semiconductor Products Group | Santa Clara, CA
Are you inspired by how algorithms and software can be used to diagnose, improve and add value to cutting edge products? Are you a natural team player who loves to solve complex problems? If so, you’ll fit right in at Applied Materials. We are a small but fast-growing team bringing domain knowledge-aided computer vision and image processing to semiconductor manufacturing. We work passionately to transform our customers’ experiences in ground-breaking ways new to this industry. You will have the guidance, tools and support you need to make this journey with us rewarding, fulfilling and fun.
Position Overview
We are seeking a highly motivated Computer Vision Research Scientist with demonstrated background and experience in developing computer vision and deep learning-based algorithms. You will be a member of the core Applied AIx team in Semiconductor Products Group (SPG), responsible for development and commercialization of all semiconductor fabrication equipment offered by Applied Materials. 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.
Job Responsibilities
- Use or develop AI and machine learning algorithms, such as one-shot/few shot learning, supervised/unsupervised learning, deep learning, reinforcement learning and others, to solve applied problems in computer vision.
- Design, prototype, validate and implementation high quality and scalable algorithms with emphasis on performance and accuracy.
- Implement algorithm designs in Python, TensorFlow, PyTorch and C/C++ with knowledge of common ML/deep learning libraries and frameworks
- Detail oriented with strong analytical, problem solving and communication skills
- Acts as mentor and resource for colleagues
- Thrives in a dynamic, startup-like environment working on high visibility initiatives
- Work with algorithm engineers and product managers to productize and optimize computer vision pipelines and integrate into our software solution
Minimum Qualifications
- MS or Ph.D. degree in Computer Science, Computer Engineer, Electrical Engineer, Mathematics, Statistics or related field
- 5+ years of industry or research experience in state-of-the-art techniques in Machine Learning, Deep Learning, Computer Vision and Image Processing
- Knowledge of Deep learning frameworks such as PyTorch, TensorFlow or Keras
- Has knowledge of industry best practices and competitive landscape
- Strong written and verbal presentation skills, both technical and non-technical audiences
- Experience of working with Scanning/Transmission Electron Microscopy images in the semiconductor industry highly desirable
Qualifications
Education:
Doctorate Degree
Skills:
Certifications:
Languages:
Years of Experience:
2 - 4 Years
Work Experience:
Additional Information
Time Type:
Full time
Employee Type:
New College Grad
Travel:
Yes, 10% of the Time
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.
