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Machine Learning Cfd Jobs in California (NOW HIRING)

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

... CFD tools, meshing software, and CAD platforms for multiphysics simulations; contribute to ... machine learning and AI solutions--such as surrogate modeling and physics-informed neural networks ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

... CFD tools, meshing software, and CAD platforms for multiphysics simulations; contribute to ... machine learning and AI solutions--such as surrogate modeling and physics-informed neural networks ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

... CFD tools, meshing software, and CAD platforms for multiphysics simulations; contribute to ... machine learning and AI solutions--such as surrogate modeling and physics-informed neural networks ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA

$145K - $175K/yr

Strong C++ software engineering skills and experience applying machine learning (ML) and AI to ... Develop and optimize next-generation software that integrates CFD tools, meshing software, and CAD ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

$145K - $175K/yr

Strong C++ software engineering skills and experience applying machine learning (ML) and AI to ... Develop and optimize next-generation software that integrates CFD tools, meshing software, and CAD ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

$145K - $175K/yr

Strong C++ software engineering skills and experience applying machine learning (ML) and AI to ... Develop and optimize next-generation software that integrates CFD tools, meshing software, and CAD ...

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Machine Learning Cfd information

What are Machine Learning CFD jobs?

Machine Learning CFD (Computational Fluid Dynamics) jobs focus on integrating machine learning techniques with traditional fluid dynamics simulations and analyses. Professionals in this field use AI and data-driven models to accelerate simulations, improve prediction accuracy, and optimize fluid flow processes. These roles often require knowledge of both CFD principles and machine learning algorithms, and are commonly found in industries such as aerospace, automotive, and energy. Typical responsibilities include developing surrogate models for simulations, automating data analysis, and implementing deep learning approaches for complex flow problems.

How does a Machine Learning CFD professional typically collaborate with domain experts and software engineers in a project setting?

As a Machine Learning CFD (Computational Fluid Dynamics) professional, you’ll frequently collaborate with domain experts such as mechanical or aerospace engineers to ensure your models accurately reflect physical phenomena. You’ll also work closely with software engineers to integrate machine learning algorithms into simulation pipelines and optimize computational performance. Effective communication is key, as you’ll need to translate complex data-driven insights into actionable engineering solutions and vice versa. These collaborative efforts help streamline workflows, improve model accuracy, and ensure practical deployment of ML-enhanced CFD tools.

What is the difference between Machine Learning CFD vs Data Scientist?

AspectMachine Learning CFDData Scientist
Required CredentialsDegree in Engineering, Computer Science, or related fields; knowledge of CFD softwareDegree in Statistics, Computer Science, or related fields; strong programming skills
Work EnvironmentEngineering firms, aerospace, automotive industries, research labsBusiness, finance, tech companies, research institutions
Industry UsageSimulation, fluid dynamics, engineering analysisData analysis, predictive modeling, business insights

Machine Learning CFD focuses on applying machine learning techniques to computational fluid dynamics simulations, often within engineering contexts. Data Scientists analyze large datasets to extract insights and build predictive models across various industries. While both roles require programming skills and a strong analytical background, Machine Learning CFD emphasizes simulation and engineering applications, whereas Data Scientists focus on data-driven decision-making across diverse sectors.

What are the key skills and qualifications needed to thrive as a Machine Learning CFD (Computational Fluid Dynamics) Engineer, and why are they important?

To thrive as a Machine Learning CFD Engineer, you need a strong background in fluid dynamics, numerical methods, and machine learning, often supported by a degree in engineering, physics, or computer science. Familiarity with CFD software (such as ANSYS Fluent or OpenFOAM), programming languages like Python or C++, and machine learning frameworks (TensorFlow or PyTorch) is essential. Critical thinking, problem-solving, and effective communication are standout soft skills for interpreting data and collaborating on interdisciplinary teams. These competencies are crucial for developing innovative solutions that enhance simulation accuracy and computational efficiency in engineering projects.
What are popular job titles related to Machine Learning Cfd jobs in California? For Machine Learning Cfd jobs in California, the most frequently searched job titles are:
What job categories do people searching Machine Learning Cfd jobs in California look for? The top searched job categories for Machine Learning Cfd jobs in California are:
What cities in California are hiring for Machine Learning Cfd jobs? Cities in California with the most Machine Learning Cfd job openings:
Machine Learning Cfd jobs near you
Senior Physics-Machine Learning Engineer - CAE

Senior Physics-Machine Learning Engineer - CAE

Nvidia

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Posted 11 days ago

Nvidia rating

9.3

Company rating: 9.3 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

15th of 209 rated software companies

Job description

NVIDIA's deep learning and HPC platforms have made a huge impact in various fields and are broadly used across leading academic institutions, start-ups, and industry, including the world's largest Internet companies. We need passionate and creative people to help us on building a AI framework that will solve the toughest and most relevant problems of humanity and problems that are at the cutting edge of science & engineering: weather/climate challenges, product design, digital twins, molecular dynamics, novel materials, accelerated drug development, etc.

What you'll be doing:

  • Collaborate with some of the brightest minds in a leading AI company to develop a leading Physics-AI framework, NVIDIA PhysicsNemo, for our academic and industrial partners to construct digital twins and machine learning simulation surrogates for real world science and engineering problems

  • Work with internal teams at Nvidia and external users to validate the product with industrial applications

  • Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new ideas to develop and enhance NVIDIA's deep learning technologies with focus on simulations

What we need to see:

  • BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience

  • 5+ yrs of relevant experience

  • Strong Python programming skills. Familiarity with containers, numeric libraries, modular software design

  • Good knowledge of state-of-the-art DNN architectures and machine learning techniques and algorithms (graph networks, diffusion models, reinforcement learning etc.) with experience in developing or using major deep learning frameworks (PyTorch, Tensorflow, JAX etc.)

  • Experience in solving and using machine learning for real world problems involving scientific/engineering simulations (multi-physics applications in CFD, structural, thermal, electrical, electromagnetics, optics, acoustics etc. for various industries such as automotive, aerospace, machinery, medical, energy, computers, semiconductors, consumer goods etc.)

  • Experience with scientific visualization is a big plus

  • Strong analytical skills with bias for action

  • Good time management and organization skills to thrive in a fast paced, dynamic environment

  • Solid written and oral communications skills. Good teamwork and interpersonal skills

Ways to stand out from the crowd:

  • Work with multi-node systems with data-parallel and model parallel programming experience

  • Experience with CUDA. Usage of nonlinear simulation tools and techniques, usage of major simulation codes (opensource and/or commercial). Development and applications of the new architectures and algorithms on industry scale problems

  • Published papers in the field of AI in scientific computing

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning - the next era of computing - with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as "the AI computing company." We're looking to grow our company and establish teams with the most thoughtful people in the world.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until July 9, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.#deeplearning

What Nvidia employees say

Hours and flexibility

Workplace

Get the full story on Breakroom

Nvidia logo

About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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