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Physics Informed Neural Networks Jobs in California

Experience applying AI to physics or simulation domains, using physics-informed neural networks (PINNs) or surrogate modeling ADDITIONAL REQUIREMENTS: * Ability to work extended hours and weekends as ...

Experience applying AI to physics or simulation domains, using physics-informed neural networks (PINNs) or surrogate modeling ADDITIONAL REQUIREMENTS: * Ability to work extended hours and weekends as ...

Experience applying AI to physics or simulation domains, using physics-informed neural networks (PINNs) or surrogate modeling ADDITIONAL REQUIREMENTS: * Ability to work extended hours and weekends as ...

NCCL, CUDA-aware MPI, NVLink topologies • Published work in neural operators, physics-informed ML, or scientific HPC • IC design domain knowledge: device physics, semiconductor materials, layout ...

Published work in neural operators, physics-informed ML, or scientific HPC * IC design domain knowledge: device physics, semiconductor materials, layout data formats

Our aim is to develop and apply a rigorous theory of latent internal structure in neural networks ... We have the beginnings of such a theory, grounded in the physics of information and experimentally ...

Software Engineer - Data

Palo Alto, CA · On-site

$175K - $275K/yr

Apply statistical techniques and empirical analysis to make informed, data-driven decisions about ... Experience in implementing or analyzing language models or neural networks PREFERRED SKILLS AND ...

Showing results 41-60

Physics Informed Neural Networks information

What is a physics informed neural network?

A Physics Informed Neural Networks (PINNs) job typically involves developing and applying neural networks that incorporate physical laws as constraints to solve complex scientific and engineering problems. Professionals in this field work on integrating differential equations into deep learning models to improve predictions and reduce the need for large training datasets. These roles are common in fields like fluid dynamics, material science, and climate modeling, where traditional computational methods can be expensive. Individuals in this role often have expertise in machine learning, numerical methods, and domain-specific physics.

What are the key skills and qualifications needed to thrive in physics informed neural networks?

To thrive in Physics Informed Neural Networks (PINNs), you need a strong background in physics, mathematics, and deep learning frameworks, typically evidenced by advanced degrees in physics, applied mathematics, computer science, or engineering. Experience with programming languages such as Python, and familiarity with libraries like TensorFlow or PyTorch, as well as experience in numerical simulation tools, are commonly required. Strong analytical thinking, problem-solving abilities, and effective communication skills help professionals excel in multidisciplinary teams. These qualifications and soft skills are essential for developing accurate, interpretable models that integrate scientific knowledge with machine learning to solve complex real-world problems.

What does a physics informed neural network do?

In a Physics Informed Neural Networks role, your daily tasks will often include designing, building, and testing neural network architectures that incorporate physical laws and constraints. You will frequently collaborate with domain experts, such as physicists or engineers, to integrate scientific knowledge into machine learning models and validate the results with real-world data. Regular responsibilities also involve coding, running experiments, analyzing results, and documenting findings for presentation or publication. This collaborative and research-driven environment helps ensure that models are both accurate and physically consistent, and offers opportunities for interdisciplinary learning and skill advancement.

What are popular job titles related to Physics Informed Neural Networks jobs in California? For Physics Informed Neural Networks jobs in California, the most frequently searched job titles are:
What job categories do people searching Physics Informed Neural Networks jobs in California look for? The top searched job categories for Physics Informed Neural Networks jobs in California are:
What cities in California are hiring for Physics Informed Neural Networks jobs? Cities in California with the most Physics Informed Neural Networks job openings:
Infographic showing various Physics Informed Neural Networks job openings in California as of August 2026, with employment types broken down into 30% Full Time, 67% Part Time, 2% Temporary, and 1% Contract. Highlights an 97% Physical, 1% Hybrid, and 2% Remote job distribution.

Sr. Software Engineer, Propulsion Simulation & Data Analysis (Raptor)

SpaceX

Hawthorne, CA

$165K - $230K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 24 days ago


SpaceX rating

8.8

Company rating: 8.8 out of 10

Based on 147 frontline employees who took The Breakroom Quiz

15th of 72 rated aerospace companies


Job description

SR. SOFTWARE ENGINEER, PROPULSION SIMULATION & DATA ANALYSIS (RAPTOR) 

The Raptor Systems Modeling and Control Team is responsible for the power-balance, optimal control, and calibration of one of the worlds most prolific and advanced rocket engines. In addition to this we aid in root cause analysis for anomaly resolution, providing data and model driven insights supporting operations and components teams in high-consequence decision making. Our models and analysis are relied upon day-in-and-day-out to evaluate the safety and optimality of flight trajectories. With hundreds of engines, hundreds of simulations, and hundreds of hot fire operations, the work we do guides both the engine design process and operation of every single mission and engine test. In this role you will work with brilliant, passionate engineers to develop rapid, seamless processes to translate engine test data into accurate predictions of future performance for the most reliable and cutting-edge rocket engines in the world. 

RESPONSIBILITIES: 

  • Maintain and improve the accuracy of the lumped-parameter thermofluid physics model of the Raptor engine
  • Conduce engine cycle analysis to steer future-state engine design and thrust upgrades
  • Conduct anomaly resolution utilizing the engine model and sparse instrumentation
  • Develop a detailed understanding of the physics underlying rocket engine performance, sources of performance variability, as well as related modeling and measurement techniques
  • Maintain and improve the accuracy of the representation of the Raptor engine used in integrated vehicle simulations, control software validation and flight Monte Carlo analysis
  • Develop tools and portals to understand the sources of engine performance variability and enact improvements to manufacturing and engine hardware design
  • Automate processes and software tools that are used to predict test performance and generate flight performance predictions for GNC (guidance, navigation, and control) and flight software
  • Collaborate with engineers across the company to extend and improve interoperability among existing tools as well as to standardize hardware and software practices, tools, and methods to maximize functionality and value while minimizing future overhead and obsolescence 

BASIC QUALIFICATIONS: 

  • Bachelor's degree in computer science, engineering, or a STEM discipline
  • 5+ year experience writing computer software
  • 5+ year experience with physics-based simulations of real dynamic systems 

PREFERRED SKILLS AND EXPERIENCE: 

  • Dynamical systems modeling
  • Experience with lumped parameter modeling of physical systems
  • Experience implementing physics-informed neural networks to solve real-world engineering problems
  • Data driven analysis of complex systems
  • Experience inferring root cause from sparse measurements
  • Demonstrable proficiency in the basic principles of compressible and incompressible flow, thermodynamics, thermochemistry, mechanics, and materials
  • Strong written and verbal communication skills, ability to make presentations to team members, internal customers and management
  • Experience building data pipelines providing sanitization, curation, visualization, exploration to high dimensional datasets
  • Experience working with or simulating combustion engines or fluid systems
  • Full stack web development experience (database design, frontend)
  • Frontend experience in Angular, React, or a similar JavaScript framework
  • Backend Development: deliver well-tested, performant, and maintainable Python, C#/.NET, C++ or Java code
  • Experience with version control, continuous integration, Unix-like operating systems
  • Experience with control feedback loop design and implementation
  • Experience with numerical analysis techniques and signal processing in multiple domains 

COMPENSATION AND BENEFITS: 

Pay range: 
Senior: $165,000.00 - $230,000.00/per year 

Your actual level and base salary will be determined on a case-by-case basis and may vary based on the following considerations: job-related knowledge and skills, education, and experience. 
Base salary is just one part of your total rewards package at SpaceX. You may also be eligible for long-term incentives, in the form of company stock, stock options, or long-term cash awards, as well as potential discretionary bonuses and the ability to purchase additional stock at a discount through an Employee Stock Purchase Plan. You will also receive access to comprehensive medical, vision, and dental coverage, access to a 401(k) retirement plan, short and long-term disability insurance, life insurance, paid parental leave, and various other discounts and perks. You may also accrue 3 weeks of paid vacation and will be eligible for 10 or more paid holidays per year. Employees accrue paid sick leave pursuant to Company policy which satisfies or exceeds the accrual, carryover, and use requirements of the law. 


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About SpaceX

Sourced by ZipRecruiter

Industry

Aerospace product and parts manufacturing, data services, guided missile and space vehicle manufacturing and satellite telecommunications

Company size

1,001 - 5,000 Employees

Headquarters location

Hawthorne, CA, US