1

Machine Learning Cfd Jobs in California (NOW HIRING)

The role involves building advanced AI systems that integrate machine learning with engineering ... CFD or FEM solvers • Experience with geometry kernels or parametric CAD APIs • Background in ...

Strong 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 ...

Strong 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 ...

Strong 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 ...

next page

Showing results 1-20

Machine Learning Cfd information

What is a machine learning CFD?

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 are the key skills and qualifications needed to thrive as a machine learning CFD 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 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 cities in California are hiring for Machine Learning Cfd jobs?

Cities in California with the most Machine Learning Cfd job openings:

Infographic showing various Machine Learning Cfd job openings in California as of August 2026, with employment types broken down into 3% Internship, 94% Full Time, and 3% Part Time. Highlights an 94% In-person, 3% Hybrid, and 3% Remote job distribution.

Senior AI Engineer - Python I FEA/CFD Surrogate Modeling

Honeywell International, Inc.

Torrance, CA • On-site

$185K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 6 days ago


Honeywell rating

8.3

Company rating: 8.3 out of 10

Based on 186 frontline employees who took The Breakroom Quiz

66th of 544 rated manufacturers


Job description


As an Advanced AI Engineer at Honeywell Aerospace, you will provide technical contributions to the development of AI-driven engineering design tools and physics-based machine learning models. This role focuses on applying artificial intelligence, physics-informed methods, and surrogate modeling to accelerate the design and analysis of aerospace mechanical systems, including wheels and brakes, fuel systems, environmental control systems, and other complex components. You will help shape the next generation of simulation and analysis capabilities by integrating AI with traditional computational tools such as CFD, FEA, and multi-physics solvers.
In this role, you will develop advanced AI surrogates and Physics-AI models, and contribute to the transition these technologies into engineering workflows across Honeywell Aerospace. You will collaborate with cross-functional teams and global research partners, pursue both internal and government research funding, and contribute to the execution from concept through integration. Your work will impact engineering efficiency, product performance, and Honeywell's leadership in AI-enabled engineering design.
You will work from our Torrance, CA location on a Hybrid schedule. No Relocation Offered.
Responsibilities
Key Responsibilities
  • Contribute to the creation of advanced Physics-AI models and surrogate models to accelerate engineering workflows for CFD, thermal analysis, structural analysis, and system-level simulation.
  • Create scripted FEA or CFD models to generate training data over parameter and load condition spaces.
    Suggest ideas to drive the AI strategy for engineering design, with a focus on physics-informed neural networks (PINNs), digital twins, and high-fidelity model surrogates.
  • Research and test new AI methodologies for multi-physics modeling of aerospace components such as engines, wheels and brakes, and mechanical actuation systems.
  • Suggest improvements to current processes for efficient data generation, data handling, and model utilization.
  • Utilize and advance state-of-the-art NVIDIA simulation and AI acceleration tools, including Physics NEMO and related model-based AI frameworks.
  • Collaborate closely with engineering teams to integrate surrogate models into design processes, enabling faster trade studies, optimization, and predictive analysis.
  • Contribute to technical execution across internal and government-sponsored R&D projects and contribute to proposal development.
  • Assist with outreach to traditional design and analysis engineering functions.

Qualifications
YOU MUST HAVE
  • Bachelor's degree from an accredited institution in a technical discipline such as science, technology, engineering, mathematics.
  • Minimum 5 years of experience with Aerospace or Mechanical Engineering.
  • Minimum 2 years of experience developing AI models for physics-based simulation, engineering analysis, multi-physics modeling, or surrogate modeling. Experience in a graduate program may be included.
  • Minimum 3 years with simulation scripting (Abaqus Python scripting interface, Ansys PyAnsys or APDL or similar open-source tools).
  • Minimum 5 years working on design and simulation of physics of engineering systems involving concepts such as Computational Fluid Dynamics or Structural Analysis.
  • Experience mentoring others in specialty areas.
  • Experience with NVIDIA's physics-accelerated AI tools such as Physics NEMO, Modulus, Warp, or similar platforms for physics-informed deep learning.

WE VALUE
  • Proficiency in Python and machine learning frameworks such as PyTorch and TensorFlow.
  • Experience with JAX for differentiable models.
  • Experience working in structured machine learning deployment environments i.e. MLOps workflows
  • Experience with CFD, structural analysis, thermal modeling, or multi-physics simulation, and the ability to couple these with AI-based surrogates.
  • Experience with AI model architectures used for surrogate modeling, such as but not limited to MeshGraphNets, Neural Operators, Physics-Informed and Physics-Attention models.
  • Experience with model visualization through tools such as PyVista, Matplotlib, Plotly, and others.
  • Awareness of considerations for deploying AI models into engineering design workflows or digital engineering ecosystems.
  • Awareness of current research in physics-informed ML, scientific machine learning, and surrogate modeling at major conferences and journals.

The annual base salary range for this position is $185,000 - $ 231,000. Please note that this salary information serves as a general guideline. Honeywell considers various factors when extending an offer, including but not limited to the scope and responsibilities of the position, the candidate's work experience, education and training, key skills, as well as market and business considerations.
Due to compliance with U.S. export control laws and regulations, candidate must be a U.S. Person, which is defined as, a U.S. citizen, a U.S. permanent resident, or have protected status in the U.S. under asylum or refugee status or have the ability to obtain an export authorization.
BENEFITS
Beyond a performance-driven salary, you'll work alongside dedicated experts on technology that's advancing aviation. As a Honeywell Aerospace employee, you're eligible for a comprehensive benefits package that includes:
  • Employer-subsidized medical, dental, vision and life insurance
  • Short-term and long-term disability coverage
  • 401(k) match, flexible spending accounts and health savings accounts
  • Employee assistance program and educational assistance
  • Parental leave and 12 paid holidays
  • Paid time off for vacation, personal and sick time

Explore your benefits: https://honeywellaerospacebenefits.com/
ABOUT HONEYWELL AEROSPACE
Join a company that's reintroducing itself to the aviation community we've helped advance for more than a century. At Honeywell Aerospace (NASDAQ: HONA), we're launching as an independent, publicly traded aerospace and defense company built on a legacy of operational excellence and mission-focused execution.
Our new brand identity pairs that heritage with real momentum, as we build technology that helps pilots navigate with confidence, aircraft operate more efficiently, and operators stay ahead of change. With our systems on board 90% of the world's aircraft, your work here has reach that's rare to find anywhere else.
Focusing on our customers, investing in innovation, and building a culture of accountability and performance is how we're shaping what comes next.
Every horizon. Every mission. Every day.
ABOUT THE BUSINESS UNIT
Honeywell Aerospace products and services are found on aircraft across commercial aviation, defense and space - from engines and cockpit electronics to cabin systems, mechanical components and connectivity solutions. Our technology helps operators fly more safely, reduce fuel consumption, improve on-time performance and deliver a better experience for the people on board.
As aviation continues to evolve, we're also developing systems to support autonomous and supersonic platforms, bringing the same focus on safety and efficiency to the next era of flight. With approximately 36,000 employees worldwide and net sales of $17.4B in 2025, Honeywell Aerospace is one of the largest dedicated aerospace companies in the world. Explore our businesses: https://www.honeywellaerospace.com
Control Systems develops the thermal and motion control systems that help aircraft take off, land safely and protect the people on board. With more than 10 million passengers per day flying on aircraft equipped with our products and more than 75% of commercial flights beginning with our engine start systems, Control Systems reaches farther across the aviation industry than most people realize.
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Posting Date: 7/21/2026
#LI-Hybrid

What Honeywell employees say

Pay

Benefits

Hours and flexibility

Workplace

Get the full story on Breakroom


Honeywell logo

About Honeywell

Sourced by ZipRecruiter

Honeywell is charging into the Industrial IoT revolution with the establishment of Honeywell Connected Enterprise (HCE), building on our heritage of invention and deep, on-the-ground industry expertise. HCE is the leading industrial disruptor, building and connecting software solutions to streamline and centralize the assets, people and processes that help our customers make smarter, more accurate business decisions. Moving at the speed of software, we are creating, innovating and delivering solutions fast, challenging the way things have always been done, piloting new ways for all of us to work, and expecting our successes to set new standards for our customers and for Honeywell. The Chief Architect for Honeywell Connected Enterprise will lead a team of architects and system engineers responsible for the design of applications and infrastructure that deliver high value outcomes for customers in industrial, buildings, distribution centers, and aerospace vertical markets. The Chief Architect will work directly with leadership, development teams, and offering management to design well integrated solutions that utilize software platforming to encourage reuse and speed to market.

Industry

Furniture manufacturing

Company size

10,000+ Employees

Headquarters location

Charlotte, NC, US

Year founded

1906