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Physics Informed Machine Learning Jobs in San Diego, CA

Qualcomm

Machine Learning R&D

San Diego, CA · On-site

Job Area: Engineering Group, Engineering Group > Machine Learning Engineering General Summary ... Physics, Neuroscience, Economics, and VLSI Design, united by our passion to solve challenging ...

Qualcomm

Machine Learning R&D

San Diego, CA · On-site

$140K - $211K/yr

Job Area: Engineering Group, Engineering Group > Machine Learning Engineering General Summary ... Physics, Neuroscience, Economics, and VLSI Design, united by our passion to solve challenging ...

Intuit

Senior Machine Learning Engineer

San Diego, CA · On-site

$171K - $231K/yr

Senior Machine Learning Engineer Join a vibrant team of machine learning engineers helping conceive ... informed. * Run and interpret A/B tests and statistical analyses to determine model and feature ...

Intuit

Senior Machine Learning Engineer

San Diego, CA · On-site

$171K - $231K/yr

Overview Senior Machine Learning Engineer Join a vibrant team of machine learning engineers helping ... informed. * Run and interpret A/B tests and statistical analyses to determine model and feature ...

Cesna Group

Computer Vision R&D Engineer

San Diego, CA · On-site

$100K - $200K/yr

... Machine Learning. * As a computer vision engineer, you will be using cutting-edge vision and AI ... physics and optics engineers. (interdisciplinary and collaboration) * - Research and develop ...

Intuit

Manager 2, AI Science

San Diego, CA · On-site

$211K - $285K/yr

In this role you will be building and deploying machine learning models using both analytical ... Physics, etc.) * 2+ plus years experience as an established technical leader/Manager of AI science ...

Intuit

Manager 2, AI Science

San Diego, CA · On-site

$211K - $285K/yr

In this role you will be building and deploying machine learning models using both analytical ... Physics, etc.) * 2+ plus years experience as an established technical leader/Manager of AI science ...

Intuit

Manager 2, AI Science

San Diego, CA · On-site

$211K - $285K/yr

In this role you will be building and deploying machine learning models using both analytical ... Physics, etc.) * 2+ plus years experience as an established technical leader/Manager of AI science ...

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How much do physics informed machine learning jobs pay per hour?

As of Sep 2, 2026, the average hourly pay for physics informed machine learning in San Diego, CA is $21.30, according to ZipRecruiter salary data. Most workers in this role earn between $13.27 and $27.07 per hour, depending on experience, location, and employer.

What is a physics informed machine learning?

A Physics Informed Machine Learning (PIML) job involves developing AI models that integrate physics-based principles to improve accuracy, interpretability, and generalization. Professionals in this role use machine learning techniques alongside domain knowledge in physics, engineering, or applied sciences to solve complex problems in areas like fluid dynamics, materials science, and climate modeling. Responsibilities often include designing algorithms, implementing simulations, and validating results against experimental or real-world data. Employers typically seek expertise in deep learning, numerical methods, and programming languages like Python.

What are the typical challenges faced by professionals working in physics informed machine learning roles?

Professionals in Physics Informed Machine Learning often encounter challenges integrating complex physical theories with advanced machine learning models, requiring deep domain knowledge and strong technical skills. Balancing model accuracy with computational efficiency and ensuring that models are both interpretable and generalizable can be demanding. Collaboration with domain experts, data scientists, and engineers is common, as projects often span multiple disciplines. Successfully navigating these challenges provides valuable experience and is highly regarded, often leading to further career advancement in research, engineering, or leadership positions.

What are the key skills and qualifications needed to thrive in the physics informed machine learning position, and why are they important?

To thrive in Physics Informed Machine Learning, you need a solid background in physics, strong mathematical and statistical skills, and experience with machine learning algorithms, typically supported by an advanced degree in a relevant field. Proficiency with programming languages like Python, frameworks such as TensorFlow or PyTorch, and familiarity with numerical simulation tools are commonly required. Effective problem-solving, clear communication, and the ability to collaborate with interdisciplinary teams make a significant impact in this role. These capabilities are essential for developing robust, interpretable machine learning models that leverage physical laws to solve complex, real-world problems.

What are popular job titles related to Physics Informed Machine Learning jobs in San Diego, CA?

For Physics Informed Machine Learning jobs in San Diego, CA, the most frequently searched job titles are:

What job categories do people searching Physics Informed Machine Learning jobs in San Diego, CA look for?

The top searched job categories for Physics Informed Machine Learning jobs in San Diego, CA are:

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Physics Informed Machine Learning jobs near you
Infographic showing various Physics Informed Machine Learning job openings in San Diego, CA as of August 2026, with employment types broken down into 6% Internship, 43% Full Time, 44% Part Time, and 7% Contract. Highlights an 100% In-person job distribution, with an average salary of $44,306 per year, or $21.3 per hour.

Physics Informed Machine Learning Scientist

ASML

San Diego, CA • On-site

Full-time

Re-posted 10 days ago

ASML rating

9.1

Company rating: 9.1 out of 10

Based on 42 frontline employees who took The Breakroom Quiz

21st of 495 rated machine equipment manufacturers

Job description

Job Summary:
ASML is a leading company in developing lithography machines for the microchip industry. They are seeking a Physics Informed Machine Learning Scientist to join a research team focused on creating next-generation lithography light source technologies through advanced data management and machine learning methodologies.
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.
• Perform other duties as assigned or required.
Qualifications:
Required:
• 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.
• 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.
Preferred:
• 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.
Company:
ASML is a manufacturer of chip-making equipment. Founded in 1984, the company is headquartered in Veldhoven, NLD, with a team of 10001+ employees. The company is currently Late Stage.

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