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Machine Learning Cfd Jobs in Virginia (NOW HIRING)

Apply advanced data science techniques with machine learning to build surrogate models of CFD simulation results. * Support the structural and thermal analysis teams by deriving pressure and ...

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

Mechanical Engineer

Lorton, VA · On-site

$91K - $116K/yr

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

Mechanical Engineer

Lorton, VA · On-site

$91K - $116K/yr

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

Mechanical Engineer

Lorton, VA · On-site

$91K - $116K/yr

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

Mechanical Engineer

Lorton, VA · On-site

$91K - $116K/yr

... machine learning (ML), and augmented reality (AR). QinetiQ US's dedicated experts in defense ... Computational Fluid Dynamics (CFD) * Experience in additive manufacturing design, methods, and ...

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 cities in Virginia are hiring for Machine Learning Cfd jobs? Cities in Virginia with the most Machine Learning Cfd job openings:
Senior Consultant - Computational Aerothermodynamics & Machine Learning

Senior Consultant - Computational Aerothermodynamics & Machine Learning

Analytical Mechanics Associates

Hampton, VA • On-site, Remote

$59 - $69/hr

Part-time

Medical, Dental, Vision, Retirement

Posted 13 days ago


Job description

Job Description:
56-$69 Analytical Mechanics Associates (AMA) is seeking a highly specialized Subject Matter Expert to serve in a part-time, advisory capacity. This consultant will provide strategic technical guidance and expert review at the intersection of computational aerothermodynamics, advanced modeling and simulation (M&S), and machine learning (ML).
Requiring a commitment of no more than 20 hours per month, this role is ideal for an established researcher, academic, or industry veteran looking to lend their expertise to cutting-edge aerospace challenges without a full-time commitment.
The hourly rate for this position is $59-$69 an hour commensurate with experience and education.
Key Responsibilities:
  • Technical Advisory: Provide expert-level consultation on computational aerothermodynamics methodologies, physics-based modeling, and simulation strategies.
  • Machine Learning Integration: Advise on the application and integration of machine learning algorithms (e.g., surrogate modeling, physics-informed neural networks, data-driven turbulence modeling) to enhance traditional CFD and aerothermodynamic workflows.
  • Design & Architecture Review: Evaluate and provide feedback on the architecture of high-performance physical models and numerical methods.
  • Strategic Roadmapping: Assist engineering teams in identifying emerging trends and state-of-the-art techniques in M&S and computational physics to maintain a competitive technical edge.
  • Mentorship & Collaboration: Serve as a sounding board for senior engineers and developers, helping to troubleshoot complex physical and algorithmic challenges.

Required Qualifications:
  • Education: Ph.D. in Aerospace Engineering, Mechanical Engineering, Physics, or a strictly related computational discipline.
  • Experience: A minimum of 5 years of active, post-Ph.D. professional experience specifically focused on computational aerothermodynamics, M&S, and ML.
  • Domain Expertise: Deep foundational knowledge of hypersonic and supersonic flows, high-temperature gas dynamics, and advanced computational fluid dynamics (CFD).
  • Machine Learning Proficiency: Proven track record of applying machine learning, deep learning, or advanced statistical modeling to complex fluid dynamics or thermodynamic problems.
  • Communication: Exceptional ability to distill complex theoretical concepts into actionable engineering guidance.

Preferred Qualifications:
  • Familiarity with modern, high-performance software architecture, particularly the development of robust C++ libraries for CFD codes (e.g., providing complex gas properties).
  • Experience with heterogeneous computing environments, including GPU acceleration and parallel programming models (e.g., OpenMP, CUDA, Kokkos).
  • Deep knowledge of physics of high-enthalpy flows, including thermal radiation, chemical kinetics, and transport processes.
  • History of peer-reviewed publications in relevant aerospace, physics, or computational science journals.

This position requires U.S. Citizenship or Permanent Residence.
Analytical Mechanics Associates (AMA) is proud of our customer relationships, our diverse and dynamic work environment, and our employees' career satisfaction. AMA is a small business with a wide reach; headquartered in Hampton, VA, AMA has operations in Greenbelt, MD; Huntsville, AL; Dallas and Houston, TX; Denver, CO; Mountain View, CA; and Edwards Air Force Base, CA. With over 60 years of experience, AMA specializes in aerospace engineering, science, analytics, information technology, and visualization solutions. AMA combines the best of engineering, science, and mathematics capabilities with the latest in information technologies, visualization, and multimedia to build creative solutions. We offer competitive salaries and a substantial benefits package, including but not limited to paid personal and federally recognized holiday leave, salary deferrals into a 401(k)-matching plan with immediate vesting, tuition reimbursement, short/long term disability plans, and a variety of medical, dental, and vision insurance options.
AMA is committed to the professional growth of every employee, understanding that the successes of our employees drive our success. We provide a work environment that is engaging, collaborative, and supportive. To learn more about our company, please visit our website at www.ama-inc.com/careers and follow us on Facebook and LinkedIn.
AMA is an Equal Opportunity Employer and does not discriminate against any applicant for employment or employee because of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or any other characteristic prohibited under federal, state, or local laws.