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Machine Learning Cfd Jobs in California (NOW HIRING)

Applied Materials

Mechanical Engineer

Santa Clara, CA · On-site

$124K - $171K/yr

We empower our team to push the boundaries of what is possible-while learning every day in a ... Experience with engineering analysis tools (e.g., ANSYS, CFD-ACE, COMSOL ) is a plus.

Amat

Mechanical Engineer

Santa Clara, CA · On-site

$124K - $171K/yr

We empower our team to push the boundaries of what is possible-while learning every day in a ... Validate solutions using firstprinciples hand calculations and simulation tools (e.g., FEA / CFD ...

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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
Infographic showing various Machine Learning Cfd job openings in California as of June 2026, with employment types broken down into 79% Full Time, 11% Part Time, 3% Temporary, 5% Contract, and 2% Nights. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.
Senior Developer Technology Engineer, Public Sector

Senior Developer Technology Engineer, Public Sector

Nvidia

Santa Clara, CA • Hybrid

$64 - $84.50/hr

Full-time

Posted 12 days ago

Job description

We are now seeking a Senior Developer Technology Engineer for the Public Sector!

NVIDIA is hiring passionate, world-class computer scientists and engineers to work in its Public Sector Developer Technology (Devtech) team! In this role, you will research and develop techniques to GPU-accelerate leading applications in the federal ecosystem, including fields such as CFD, Electronic Design Automation, Graph Theory, Weather/Climate Modeling, and AI in HPC. You will be performing in-depth analysis and optimization to ensure the best possible performance on current and next-generation GPU architectures.

What you'll be doing:

  • Working directly with key application developers to understand the current and future problems they are solving, crafting and optimizing core parallel algorithms and data structures to provide the best solutions using GPUs, through reference code development, direct contribution to the full software stack including libraries, applications.

  • Collaborating closely with diverse groups at NVIDIA such as the architecture, research, libraries, tools, and system software teams to influence the design of architectures, software, and programming models, by investigating the impact on application performance and developer productivity.

  • Occasional travel from time to time for conferences and on-site visits with developers.

What we need to see:

  • Have an MS or PhD degree or equivalent experience in Computer Science, Engineering or STEM field.

  • Programming fluency in C/C++ with a deep understanding of software design, programming techniques, and algorithms.

  • 5+ years of relevant work experience with parallel programming, ideally CUDA C/C++, OpenMP or MPI, or SHMEM (OpenSHMEM or NVSHMEM).

  • Strong computer science fundamentals, ideally including parallel data structures and algorithms, combinatorics, and sparse representations.

  • Passion for optimizing codes to run exceptionally fast through parallel programming.

Ways to stand out from the crowd:

  • Experience optimizing complex codes, especially for GPUs, including kernel optimization and strong understanding of how software runs on hardware. A background with algorithm and architecture codesign is a plus.

  • Domain expertise in any of the following: electronic design automation, high-performance computing, computational fluid dynamics, data and graph analytics, data-science, network analysis, machine learning, or deep learning.

  • Experience in profiling and optimizing applications and frameworks including experience with Nsight Systems and Nsight Compute.

  • Experience in developing or optimizing workflows involving HPC and AI models.

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA's GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team!NVIDIA is widely considered to be one of the world's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you are creative and like making code run as fast as possible through a combination of critical thinking, profiling, and hardware and software knowledge, we want to hear from you

#LI-Hybrid

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until April 13, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse 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.
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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