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Machine Learning Cfd Jobs in Austin, TX (NOW HIRING)

Meta

Mechanical Engineer, Infrastructure

Austin, TX

$118K/yr

Experience optimizing product designs using FEA and CFD for shock and vibration, thermal, and ... Familiar with AI/ML, server, storage, network, machine learning systems About Meta: Meta builds ...

Eosgroup

R&D Engineer

Pflugerville, TX · On-site

... CFD, FEA) and programming skills (e.g., Python). Experience with machine learning models and API programming is a plus. R&D mindset with the will to learn, develop and improve work practices and ...

EOS

R&D Engineer

Pflugerville, TX · On-site

... e.g., CFD, FEA) and programming skills (e.g., Python). Experience with machine learning models and API programming is a plus. • R&D mindset with the will to learn, develop and improve work ...

All JobsMachine Learning Cfd JobsMachine Learning Cfd Jobs in Austin, TX

Machine Learning Cfd information

See Austin, TX salary details

$10.9K

$92.2K

$130.8K

How much do machine learning cfd jobs pay per year?

As of Aug 24, 2026, the average yearly pay for machine learning cfd in Austin, TX is $92,197.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,700.00 and $109,000.00 per year, depending on experience, location, and employer.

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 are popular job titles related to Machine Learning Cfd jobs in Austin, TX?

For Machine Learning Cfd jobs in Austin, TX, the most frequently searched job titles are:

What job categories do people searching Machine Learning Cfd jobs in Austin, TX look for?

The top searched job categories for Machine Learning Cfd jobs in Austin, TX are:

What cities near Austin, TX are hiring for Machine Learning Cfd jobs?

Cities near Austin, TX with the most Machine Learning Cfd job openings:

Machine Learning Cfd jobs near you

Mechanical Engineer, Infrastructure

Meta

Austin, TX

$118K/yr

Full-time

Posted 18 days ago

Meta rating

7.8

Company rating: 7.8 out of 10

Based on 45 frontline employees who took The Breakroom Quiz

139th of 246 rated software companies

Job description

This is a full-time position within the Mechanical Engineering group The Infra Mechanical Engineering group supports all the product teams, such as AI/ML, servers, storage, networking, Rack&Power and data centers. Each product team is responsible for building a specific piece of the infrastructure to connect people across the world. Meta supports this effort through the Open Compute Project (OCP). This is a unique opportunity to join our team and help us build the world’s most open and efficient connection platforms.
Mechanical Engineer, Infrastructure Responsibilities:
  • Specifications, design, prototyping, and testing of devices and products for AI/ML, server, storage, network systems, or Rack & Power, for use in communication devices and data centers
  • Work closely with the TPM, hardware, thermal, software, supply chain and outside partner teams to ensure that project goals and schedules are met
  • Validate product performance against requirements from many internal customers using design and simulation tools
  • Perform part and assembly-level tolerance analysis, motion, and performance studies
  • Quickly iterate through various design concepts, bringing them to life via fast prototypes that can be fabricated with assistance from our prototyping lab
  • Create test plans, design test equipment, and undertake testing procedures to verify design performance
  • Create documentation and specifications suitable for prototyping, quoting, and production
  • Work with contract manufacturing partners through the design-for-manufacturing process and engineering verification stages required to move the product from prototype to production
  • Support our manufacturing partners by working on-site with their overseas design and manufacturing teams

Minimum Qualifications:
  • Bachelor’s degree in mechanical or mechatronic engineering or equivalent industry experience
  • 3+ years of experience in designing and shipping volume commercial products
  • Experience with 3D CAD software such as SolidWorks or Creo
  • Experience with analyzing and resolving issues cross-functionally
  • Communication and documentation experience

Preferred Qualifications:
  • Experience designing sheetmetal enclosures
  • Experience with detailed tolerance analysis of complex assemblies
  • Experience designing plastic, die cast, extruded, and machined parts
  • Experience optimizing product designs using FEA and CFD for shock and vibration, thermal, and certification performance
  • 5+ years of experience in designing and shipping data center system equipment
  • Experience with a variety of electronic interconnections and their various performance pros and cons
  • Experience with environmental qualification testing and industry qualification testing
  • Experience with owning a complete hardware system as a mechanical engineering lead
  • End-to-end experience from concept creation to deployment of a product
  • Familiar with AI/ML, server, storage, network, machine learning systems

About Meta:
Meta builds technologies that help people connect, find communities, and grow businesses. When Facebook launched in 2004, it changed the way people connect. Apps like Messenger, Instagram and WhatsApp further empowered billions around the world. Now, Meta is moving beyond 2D screens toward immersive experiences like augmented and virtual reality to help build the next evolution in social technology. People who choose to build their careers by building with us at Meta help shape a future that will take us beyond what digital connection makes possible today—beyond the constraints of screens, the limits of distance, and even the rules of physics.
Meta is proud to be an Equal Employment Opportunity and Affirmative Action employer. We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender, gender identity, gender expression, transgender status, sexual stereotypes, age, status as a protected veteran, status as an individual with a disability, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Meta participates in the E-Verify program in certain locations, as required by law. Please note that Meta may leverage artificial intelligence and machine learning technologies in connection with applications for employment.
Meta is committed to providing reasonable accommodations for candidates with disabilities in our recruiting process. If you need any assistance or accommodations due to a disability, please let us know at accommodations-ext@meta.com.
$118,000/year to $170,000/year + bonus + equity + benefits
Individual compensation is determined by skills, qualifications, experience, and location. Compensation details listed in this posting reflect the base hourly rate, monthly rate, or annual salary only, and do not include bonus, equity or sales incentives, if applicable. In addition to base compensation, Meta offers benefits. Learn more about benefits at Meta.

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