In this senior role, you will lead in-house machine learning efforts for defect engineering systems at a high-throughput semiconductor manufacturing site. The position focuses on delivering real-time defect detection and classification through the full ML lifecycle, with an emphasis on deployment reliability for continuous operations.
Role Overview
As a Senior Machine Learning Engineer, you will own model development from design through production deployment and ongoing maintenance. You will drive improvements in model accuracy and time-to-detection for defect-related workflows, while mentoring engineers and setting engineering standards for code quality and design practices.
Responsibilities
- Lead the design and implementation of advanced ML models for defect detection and classification, optimizing for accuracy, throughput, and minimal time-to-detection.
- Collaborate with expert module owners to translate complex physical defect characteristics into mathematical modeling proposals and rigorous classification frameworks.
- Drive the transition from research to production by evaluating emerging AI research and whitepapers and adapting new architectures to semiconductor manufacturing challenges.
- Improve performance using feature engineering, hyperparameter tuning, and modern vision architectures such as CNNs and object detection.
- Develop and maintain models capable of operating reliably in a 24/7 production environment with seamless integration.
- Set expectations for codebase quality and group design principles, provide technical mentorship to junior engineers, and conduct rigorous code reviews.
Requirements
- BS or MS in Software Engineering, Computer Science, Data Science, Mathematics, or a related STEM/Engineering degree.
- 5+ years of relevant experience.
- Semiconductor industry experience is highly preferred.
- Strong command of open-source ML frameworks including TensorFlow 2.x and PyTorch, with demonstrated experience deploying models into production.
- Comfort working with command-line interfaces and Linux environments (Ubuntu), including understanding how to optimize models for hardware performance.
- Ability to convert complex ML metrics into actionable insights for a range of audiences, from engineers to site leadership.
- Proven experience managing complex technical projects from conception to delivery while meeting strict deadlines and following sound software design principles.
Technologies
- TensorFlow 2.x
- PyTorch
- CNNs
- Object Detection
- Linux
- Ubuntu
Compensation and Location
Location: Taylor, TX (onsite). Base salary range: USD 106,000 - 145,000 per year.
All positions at Samsung Austin Semiconductor are full-time on-site. Total compensation includes a competitive benefits package and may include participation in company incentive compensation programs.
Benefits
- Medical, dental, and vision insurance
- Life insurance and 401(k) matching with immediate vesting
- Onsite cafe(s) and workout facilities
- Paid maternity and paternity leave
- Paid time off (PTO) + 2 personal holidays and 10 regular holidays
- Wellness incentives and MORE
- MBO bonuses based on company, division, and individual performance
- Competitive benefits package and may include participation in company incentive compensation programs
Trade Secret Notice
By submitting an application, you agree not to disclose to Samsung or induce or encourage Samsung to use any confidential or proprietary information, including trade secrets, belonging to a current or former employer or other entity.
