Staff Machine Learning Engineer

Introduction

ASML US, including its affiliates and subsidiaries, bring together the most creative minds in science and technology to develop lithography machines that are key to producing faster, cheaper, more energy-efficient microchips. We design, develop, integrate, market, and service these advanced machines, which enable our customers - the world’s leading chipmakers - to reduce the size and increase the functionality of their microchips, which in turn leads to smaller, more powerful consumer electronics. Our headquarters are in Veldhoven, Netherlands, and we have 18 office locations around the United States including main offices in Chandler, Arizona, San Jose and San Diego, California, Wilton, Connecticut, and Hillsboro, Oregon.

Job Mission

The EUV source team in San Diego operates in a fast-paced, uniquely innovative and challenging environment to create new-to-industry solutions with rapid productization to support an aggressive commercialization plan for the EUV technology within ASML. The Controls Department is responsible for the development and engineering of the control loops for the EUV light source system.  The EUV light source system is a complex and challenging system that requires sophisticated control algorithms, real-time embedded software, high speed electronics, and precision sensors to produce stable EUV light under dynamic conditions.

We are in search of an accomplished and driven Machine Learning Engineer who has a robust understanding of Large Language Models and Generative AI. Your primary role will involve decoding and applying groundbreaking research and setting the course for the team in this thriving field. This Machine Learning Engineer  is a key enabler to further develop the site’s AI competence. 

Duties and Responsibilities

• Performs the design, development, and implementation of complex algorithms involving controller design, system identification, signal processing and dataset analysis  using Artificial Intelligence and Machine Learning techniques.

• Work on a wide variety of AI projects, such as physics based model development, machine learning, Gen-AI, for the development of the EUV source, and partner with engineering teams to integrate ML models and solutions, ensuring performance optimization and alignment with broader Product goals.

• Leading the exploration and application of Large Language Models and Generative AI, venturing into new areas within these fields.
• Actively engaging in all aspects of model development, from ideation and experimentation to deployment.
• Work with large-scale data sets and intensive hand-on algorithm development
• Develop and implement complex algorithms for controller design, system identification, signal processing and dataset analysis using AI and ML techniques.
• Apply scientific and mathematical control design principles and concepts to potential inventions and products, using ML techniques and tools. Conduct laboratory research on algorithm design and validation, as well as ML model development and evaluation.
• Set the team's strategic direction, foster an environment that promotes innovation and professional growth.
• Other duties as assigned.

Automation/Algorithms/Controls Specific

• Works from broadly defined systems specifications to determine appropriate top-down automation, control system and algorithm architecture.
• Generates software and /or firmware requirements for control algorithm implementations
• Plans and executes laboratory research pertaining to algorithm design and validation in lab test bench and/or cleanroom
• Designs and builds tools that allow debugging, analysis and performance evaluation of algorithms
• Mentors more junior level algorithm engineers through technical guidance and assistance.

Skills

• Experience with optimization, approximation algorithms, deep learning, and hands-on implementation of these techniques.
• Ability to translate, statistically analyze large amounts of data and effectively report problems through written and/or graphical formats.
• Comprehensive knowledge and hands-on experience with fine-tuning approaches and training models.
• Proven problem-solving and leadership abilities, with the capacity to steer the team's research and practical applications in a collaborative and fast-paced environment.
• Experienced in one or more of the following ML areas: Computer Vision, NLP, GenAi, AR/VR, Document Intelligence, or similar areas.
• In-depth experience in Machine Learning, with a particular emphasis on Large Language Models (LLMs) and Generative AI.
• Experience with deep learning framework such as Pytorch, TensorFlow and Keras.
• Published research in the field of Machi