Physics Informed Machine Learning Scientist

ASML; San Diego (CA); On-site; USD 135,375 - 203,063; Full time

Benefits offered by this job

Medical, dental, vision insurance

401k plan

Vacation leave

Job summary

ASML in San Diego seeks a Physics Informed Machine Learning Scientist to join a pioneering research team. The role involves developing and optimizing integrated master-model frameworks for lithography technologies.

The successful candidate will have a Ph.D. or Master’s degree with extensive experience, strong software skills, and a background in data management. ASML offers competitive compensation and benefits, emphasizing a diverse and inclusive workplace.

Qualifications

• Minimum 3 years of experience in an analytical field.
• Extensive experience in physics-informed machine learning.
• Strong expertise in data management and pipelines.

Responsibilities

• Establish data management frameworks for ML workflows.
• Develop machine learning models and scientific simulations.
• Document learnings and communicate with teams.

Skills

Physics-informed machine learning

Data management

Python

Deep learning frameworks

C/C++

Education

Ph.D. in a relevant field

Master’s degree with 6+ years of experience

Tools

PyTorch

JAX

MLflow

Job description

ASML US, LP brings 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, the Netherlands, and we have 18 office locations around the United States including main offices in Wilton, CT, Chandler, AZ, San Jose, CA and San Diego, CA.

Job Mission

Join a pioneering research team developing next‑generation lithography light source technologies. Our laser‑produced plasma (LPP) system integrates high‑power lasers, advanced optics, plasma‑based EUV generation, sensing, and algorithm‑driven control. The Physics Informed Machine Learning Scientist works on the Virtual Source team building integrated master‑model frameworks to capture the tightly coupled, multi‑physics behavior of the system—enabling system‑level optimization, reducing uncertainty in future source configurations, and guiding early technology decisions. This role operates at the intersection of science, engineering, and modeling to define future source architectures. You will contribute by building data pipelines, developing data analysis and ML methodologies, integrating and advancing models, and defining validation experiments on test benches and research systems to anchor Virtual Source.

Key Responsibilities

• Establish a scalable data management framework spanning legacy and new datasets from test benches and source prototypes, ensuring data quality, accessibility, and structured readiness for seamless integration into ML workflows.
• Develop physics‑informed machine learning models and scientific simulations to enable system‑level tradeoff analysis and drive the definition and optimization of lithography source technology configurations.
• Adapt and integrate existing physics‑based models into a master virtual model, and establish the necessary infrastructure for deployment and maintenance.
• Propose experimental anchoring studies, analyze test results, reduce model uncertainty through correlation building, and extract actionable knowledge from submodule‑to full‑system‑level analysis.
• Provide input to technology roadmaps, identify de‑risking activities and key scientific learning objectives, and contribute to experimental design to establish design guidelines, performance requirements, and procedures for product teams.
• Troubleshoot code and algorithms required for source operation, data streaming, storage, and queries.
• Document learnings and communicate knowledge to engineering and product development teams to guide product improvement and the release of new product nodes.
• Work independently and collaboratively to deliver on stated objectives, whether pursuing new knowledge, demonstrating new capabilities, or characterizing existing performance.

Qualifications

• Ph.D. with a minimum of 3+ years of experience or a Master’s degree with at least 6+ years of experience in an analytical field such as mathematics, physics, or engineering, with extensive experience in physics‑informed machine learning and model integration into scalable master models.
• Experience solving complex, open‑ended modeling problems using optimization and deep learning methodologies, with strong expertise in data management and building scalable data and training pipelines for end‑to‑end model development and training.
• Strong software development skills in Python, with experience in deep learning frameworks (e.g. PyTorch or JAX); proficiency in C/C++, and Matlab is a plus. Experience with database tools, automation frameworks, and experimental tracking platforms (e.g. MLflow) for managing end‑to‑end ML lifecycle.
• Experience working in cloud and development environments such as Azure Kubernetes Service (AKS), Google Distributed Cloud Edge (GDCE), Apache Spark, Azure Databricks, and related technologies is a plus.

Skills

• Ability to clearly and logically communicate ideas and knowledge to various audiences.
• Demonstrated ability to work effectively as a part of a team and lead investigation and research efforts involving multiple stakeholders and constraints.
• Proven ability to build trust and credibility, enabling effective leadership through influence.
• The successful candidate will not only have excelled in their technical field, but will have demonstrated inter‑personal and communications strengths.
• Deep understanding of scientific research methods and strong curiosity.

Physical Demands and Work Environment

• While performing the duties of this job, the employee routinely is required to sit; walk; talk; hear; use hands to keyboard, finger, handle, and feel; stoop, kneel, crouch, twist, reach, and stretch.
• The employee is occasionally required to move around the campus including working while fully gowned in a clean room environment.
• The employee may occasionally lift and/or move up to 25 pounds.
• The employee may be required to travel based on business needs.
• Specific vision abilities required by this job include close vision, color vision, peripheral vision, depth perception, and ability to adjust focus.
• The environment generally is moderate in temperature and noise level.
• Extended periods of time in a clean room environment should be expected. Requires gowning in Class 10K gowning protocol.
• May need to work in labs with equipment that emit high‑pitched noise.
• May spend extended periods of time at a computer workstation.

Compensation and Benefits

The current base annual salary range for this role is $135,375-203,063.

Pay scales are determined by role, level, location and alignment with market data. Individual pay is determined through interviews and an assessment of several factors that are unique to each candidate, including but not limited to job‑related skills, relevant education and experience, certifications, abilities of the candidate and pay relative to other team members.

The Company offers employees and their families, medical, dental, vision, and basic life insurance. Employees are able to participate in the Company’s 401k plan. Employees will also receive eight (8) hours of vacation leave every month and (13) paid holidays throughout the calendar year.

Controlled Technology Access

This position requires access to controlled technology, as defined in the United States Export Administration Regulations (15 C.F.R. 730, et seq.). Qualified candidates must be legally authorized to access such controlled technology prior to beginning work. Business demands may require ASML to proceed with candidates who are immediately eligible to access controlled technology.

Inclusion and Diversity

ASML is an Equal Opportunity Employer that values and respects the importance of a diverse and inclusive workforce. It is the policy of the company to recruit, hire, train and promote persons in all job titles without regard to race, color, religion, sex, age, national origin, veteran status, disability, sexual orientation, or gender identity. We recognize that inclusion and diversity is a driving force in the success of our company.

Request an Accommodation

ASML provides reasonable accommodations to applicants for ASML employment and ASML employees with disabilities. An accommodation is a change in work rules, facilities, or conditions which enable an individual with a disability to apply for a job, perform the essential functions of a job, and/or enjoy equal access to the benefits and privileges of employment. If you are in need of an accommodation to complete an application, participate in an interview, or otherwise participate in the employee pre‑selection process, please send an email to [e-mail] to initiate the company’s reasonable accommodation process.

Please note: Any recruitment questions should be directed to the designated Talent Acquisition member for the position.