AI/ML Image Processing Engineer

KLA Corporation

Milpitas (CA)

On-site

USD 136,000 - 232,000

Full time

3 days ago
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Benefits offered by this job

Medical
Dental
Vision
Life Insurance
401(k) matching
ESPP
Student debt assistance
Tuition reimbursement
Career development programs
Wellness program
PTO & holidays
Family leave

Job summary

KLA Corporation in Milpitas, CA seeks a highly skilled ML/DL/Computer Vision engineer to advance high-throughput inspection systems. You will design, prototype, and deploy advanced algorithms for image and signal processing in production environments.

Collaborate with software, systems, and field teams to improve robustness, scalability and maintainability, influence architecture decisions, and push the boundaries of AI-enabled semiconductor manufacturing.

Qualifications

  • Doctorate (Academic) degree or equivalent with strong research background.
  • Master's degree with related work experience (3 years).
  • Bachelor's degree with related work experience (5 years).
  • Hands-on experience with ML/DL frameworks and production deployments.

Responsibilities

  • Design, develop, and optimize ML/DL algorithms for complex image and signal processing tasks.
  • Own algorithm development from concept to production deployment.
  • Invent and evaluate novel computer vision approaches for real-world datasets.
  • Analyze system performance, debug issues, and improve robustness in production.
  • Collaborate with software, systems, applications, and field engineers to deliver high-quality solutions.
  • Contribute to architectural decisions and improve algorithm performance and maintainability.

Skills

Machine Learning
Deep Learning
Computer Vision
Image Processing

Education

Doctorate
Master's degree
Bachelor's degree

Tools

TensorFlow
PyTorch

Job description

KLA Corporation in Milpitas, CA seeks a highly skilled ML/DL/Computer Vision engineer to advance high-throughput inspection systems. You will design, prototype, and deploy advanced algorithms for image and signal processing in production environments.

Collaborate with software, systems, and field teams to improve robustness, scalability and maintainability, influence architecture decisions, and push the boundaries of AI-enabled semiconductor manufacturing.

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