ZipRecruiter

Log In

1

Machine Learning Cfd Jobs in California (NOW HIRING)

Rivian

Fluid Dynamics Engineer

Irvine, CA

$95K - $106K/yr

Execute high-fidelity CFD campaigns across Aerodynamics, Soiling, and Water Management to optimize ... Leverage machine learning and advanced scripting to automate simulation post-processing ...

Rivian

Fluid Dynamics Engineer

Irvine, CA · On-site

$95K - $106K/yr

Execute high-fidelity CFD campaigns across Aerodynamics, Soiling, and Water Management to optimize ... Leverage machine learning and advanced scripting to automate simulation post-processing ...

Rivian

Fluid Dynamics Engineer

Irvine, CA · On-site

$95K - $106K/yr

Execute high-fidelity CFD campaigns across Aerodynamics, Soiling, and Water Management to optimize ... Leverage machine learning and advanced scripting to automate simulation post-processing ...

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 ...

Amat

Mechanical Engineer IV

Santa Clara, CA

$147K - $202K/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 ...

next page

Showing results 1-20

All JobsMachine Learning Cfd JobsMachine Learning Cfd Jobs in California

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
Aerodynamics Engineer, Modeling and Optimization

Aerodynamics Engineer, Modeling and Optimization

Archer

San Jose, CA • On-site

$140K - $190K/yr

Other

Posted 13 days ago

Job description

What you'll do:

  • Perform low/mid/high fidelity aerodynamic simulations of Archer eVTOL aircraft
  • Develop linear/non-linear aerodynamic models to predict aircraft behavior and performance throughout the flight envelope
  • Analyze experimental data (either from flight test or wind tunnel) to identify sources of model errors, validate, and improve aerodynamic models of the vehicle
  • Develop efficient methods to feed flight test data back into aerodynamic simulation models of various fidelity and complexity
  • Contribute to the development of Archer aerodynamic software stack, improving methods and workflows
  • Coordinate with other cross-functional teams and pilots for flight simulator aerodynamic modeling updates and issue resolution

What you need:

  • BS / MS / PhD in Aerospace Engineering or a related field
  • 2+ years of experience with BS, or 1+ years of experience with MS, or 1+ years of experience with PhD modeling rotorcraft, tiltrotor, eVTOL aerodynamics at full-vehicle level
  • Strong understanding of fundamentals of fixed-wing and rotorcraft aerodynamics, performance, stability & control
  • Experience in eVTOL and/or multicopter vehicle aerodynamics design and analysis, including 6 DoF vehicle trimming and trajectory optimization
  • Experience with gradient-based and gradient-free optimization techniques
  • Experience with surrogate modeling techniques (like Kriging methods) and statistical analysis
  • Experience with experimental data processing and reduction techniques
  • Proficiency in Python programming
  • Experience with software development, object-oriented, version control best practices, as well as Git, CICD, Conda
  • Excellent work planning and issue resolution skills
  • Strong technical, written, and verbal communication skills
  • Ability to work in groups and individually
  • Experience in a fast-paced design environment

Bonus Qualifications:

  • Experience with developing, training, and optimizing neural networks or other machine learning models in the context of aerodynamic modeling
  • Experience with wind tunnel and flight test campaigns planning, execution, and data processing, ideally matured on rotorcraft, tiltrotor, eVTOL program
  • Work experience with rotorcraft comprehensive analysis tools, such as RCAS or CAMRAD2
  • Work experience with NASA Overflow and Fun3D CFD software, including meshing
  • Experience utilizing high-performance computing (HPC) to parallelize workflows
  • Familiarity with conventional airplane Part 23/25 or rotorcraft Part 27/29 certification basis and test methods
  • Familiarity with ASTM standards for fixed wing and rotorcraft
  • Familiarity with Matlab/Simulink, and Fortran/C++ coding
At Archer we aim to attract, retain, and motivate talent that possess the skills and leadership necessary to grow our business. We drive a pay-for-performance culture and reward performance that supports the Company's business strategy. For this position we are targeting a base pay between $140,000 - $190,000. Actual compensation offered will be determined by factors such as job-related knowledge, skills, and experience.Archer is committed to working with and providing reasonable accommodations to job applicants with physical or mental disabilities, and those with sincerely held religious beliefs. Applicants who may require reasonable accommodation for any part of the application or hiring process should provide their name and contact information to Archer's People Team at people@archer.com. Reasonable accommodations will be determined on a case-by-case basis.

Apply