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Machine Learning Cfd Jobs in Lawrenceville, GA (NOW HIRING)

Machine Learning Cfd information

See Lawrenceville, GA salary details

$10.1K

$85.2K

$121K

How much do machine learning cfd jobs pay per year?

As of Aug 24, 2026, the average yearly pay for machine learning cfd in Lawrenceville, GA is $85,231.00, according to ZipRecruiter salary data. Most workers in this role earn between $78,300.00 and $100,800.00 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 job categories do people searching Machine Learning Cfd jobs in Lawrenceville, GA look for?

The top searched job categories for Machine Learning Cfd jobs in Lawrenceville, GA are:

What cities near Lawrenceville, GA are hiring for Machine Learning Cfd jobs?

Cities near Lawrenceville, GA with the most Machine Learning Cfd job openings:

Senior Mechanical Engineer, Cooling System Modular Design

Google

Atlanta, GA • On-site

$86K - $119K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted yesterday

New


Google rating

8.8

Company rating: 8.8 out of 10

Based on 103 frontline employees who took The Breakroom Quiz

49th of 246 rated software companies


Job description

info_outline
X In accordance with Washington state law, we are highlighting our comprehensive benefits package, which is available to all eligible US based employees. Benefits for this role include:
  • Health, dental, vision, life, disability insurance
  • Retirement Benefits: 401(k) with company match
  • Paid Time Off: 20 days of vacation per year, accruing at a rate of 6.15 hours per pay period for the first five years of employment
  • Sick Time: 40 hours/year (increased to 69 hours/year for Seattle) including 5 discretionary sick days per instance
  • Maternity Leave (Short-Term Disability Baby Bonding): 28-30 weeks
  • Baby Bonding Leave: 18 weeks
  • Holidays: 13 paid days per year

Note: By applying to this position you will have an opportunity to share your preferred working location from the following: Atlanta, GA, USA; Reno, NV, USA; Austin, TX, USA; Kirkland, WA, USA; New York, NY, USA; Reston, VA, USA.
Minimum qualifications:
  • Bachelor's degree in Mechanical or Industrial Engineering, related discipline, or equivalent practical experience.
  • 10 years of experience in mission-critical facility design and construction environments.
  • Experience using software tooling to conduct thermal analysis, computational fluid dynamics (CFD), or hydraulic modeling for air and waterside systems.
  • Experience collaborating with cross-functional teams (e.g., operations, construction, or planning) to develop technical project documentation, specifications, or commissioning plans.

Preferred qualifications:
  • Master's degree in Mechanical Engineering, a Professional Engineering (PE) license, or equivalent advanced technical credentials.
  • Experience with offsite modular construction, pre-fabrication methodologies, and off-site commissioning strategies in large-scale industrial or mission-critical environments.
  • Experience with flushing critical cooling fluid systems including piping and equipment.
  • Experience working with specialized engineering software such as Cadence Reality DC Design, AFT Fathom or AutoPipe.
  • Excellent communication skills, able to work in teams and matrix organization.

About the job
Our thirst for technology is a part of everything we do. The Data Center Engineering team takes the physical design of our data centers into the future. Our lab mirrors a research and development department -- cutting-edge strategies are born, tested and tested again. Along with a team of great minds, you take on complex topics like how we use power or how to run state-of-the-art, environmentally-friendly facilities. You're a visionary who optimizes for efficiencies and never stops seeking improvements -- even small changes that can make a huge impact. You generate ideas, communicate recommendations to senior-level executives and drive implementation alongside facilities technicians.
With your technical expertise, you ensure compliance with codes and standards, develop infrastructure improvements and serve as an expert in your specialty (e.g., cooling, electrical).
As a Mechanical Engineer within the Data Center Technology Systems team, you will serve as a technical lead for our global mechanical infrastructure. You will pioneer next-generation cooling systems, innovating custom components and integrating modular design and pre-fabrication strategies to accelerate construction. You will collaborate across Planning, Operations, and Execution teams, lead new technologies to optimize future products for Google's machine learning fleet.
You will leverage advanced software tools to conduct detailed thermal analysis, computational fluid dynamics, and hydraulic modeling of complex air and waterside systems. Your deep understanding of thermodynamics will drive the creation of critical engineering specifications and commissioning plans. You will deliver actionable recommendations to cross-functional partners, ensuring data center scalability and efficiency.The AI and Infrastructure team is redefining what's possible. We empower Google customers with breakthrough capabilities and insights by delivering AI and Infrastructure at unparalleled scale, efficiency, reliability and velocity. Our customers include Googlers, Google Cloud customers, and billions of Google users worldwide.
We're behind Google's groundbreaking innovations, empowering the development of AI models, delivering unparalleled computing power to global services, and providing the essential platforms that enable developers to build the future. From software to hardware our teams are shaping the future of world-leading hyperscale computing, with key teams working on the development of our TPUs, Vertex AI for Google Cloud, Google Global Networking, Data Center operations, systems research, and much more.Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
US: $171000 - $247000 (USD) 20% bonus target equity benefits
Learn more about benefits at Google .
Responsibilities
  • Serve as the technical lead for global mechanical infrastructure, leading the design, testing, and deployment of custom data center cooling components and next-generation technologies.
  • Implement offsite modular construction and pre-fabrication strategies to streamline deployment timelines and improve infrastructure scalability.
  • Conduct detailed thermal analysis, computational fluid dynamics (CFD), and hydraulic modeling of complex air and waterside systems to validate proposed technologies.
  • Collaborate with Planning, Operations, and Execution teams to optimize the fleet and integrate complex mechanical systems parallel to project schedules to support machine learning demands.
  • Prepare and deliver comprehensive engineering project packages, including statements of work, product specifications, drawings, and commissioning test plans.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google's Applicant and Candidate Privacy Policy .
Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .
If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form .
Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.
To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.
Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

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