Machine Learning Mathematics Engineer

Job Overview

Join ASML as a Machine Learning Mathematics Engineer and become a part of a leading company in the semiconductor industry. In this role, you will tackle algorithm design challenges for semiconductor metrology, focusing on time, accuracy, and memory requirements. You will leverage your expertise in physics, numerical mathematics, and machine learning to solve practical problems within a talented group of algorithm experts.

Role and Responsibilities

As a Machine Learning Mathematics Engineer, you will:

• Develop optical metrology solutions using statistically correct parameter inference, machine learning, and optimization algorithms.
• Implement machine learning and deep learning metrology applications with a focus on scalable, data-intensive, and distributed software architectures.
• Collaborate with data science, functional, and software groups to ensure high-quality data and code.
• Communicate complex physical principles and algorithm solutions clearly to stakeholders.
• Design and realize proof-of-concept subsystems that meet system specifications, costs, and project planning.
• Review technical analyses and structure team contributions.
• Contribute to technical product roadmaps and generate intellectual property.

Education and Experience

To excel in this role, you should have:

• A Ph.D. in Applied Mathematics, Physics, Computer Science, or Electrical Engineering.
• Experience in numerically stable modeling and code development using sound physical-mathematical principles.
• Proficiency in Python, Julia, MATLAB, or C++.
• A strong understanding of optics, linear algebra, probability theory, robust optimization, and machine learning methods.

Skills

• Creative problem-solving with a focus on the bigger picture.
• Ability to work independently and make decisive actions in ambiguous environments.
• Strong teamwork skills and the ability to influence without authority.
• A pragmatic approach with a proactive attitude and a focus on results.

Keywords

• Deep learning pipeline
• Data-intensive and distributed computing
• Cloud computing
• Data processing
• Parameter inference
• (Non-)convex optimization
• Physics
• Software
• Dataflow
• Robust (un)supervised and reinforcement learning
• Neural network
• Inverse problem
• Physical calibration
• Mathematics
• Optics
• Regression
• Information theory

Diversity and Inclusion

ASML is an Equal Opportunity Employer that values diversity and inclusion. We recruit, hire, train, and promote individuals without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We believe that diversity and inclusion drive our success.

Additional Information

This position requires access to controlled technology as defined in the Export Administration Regulations. Qualified candidates must be legally authorized to access such technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.