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Machine Learning Cfd Jobs in Harrison, NY (NOW HIRING)

PhysicsX

Principal CFD Engineer

Manhattan, NY · On-site

$100 - $130/hr

  • Retirement

  • PTO

You're confident setting up CFD simulations independently, interpreting complex results with depth ... This Role In this role, you'll work closely with our Data Scientists, Machine Learning Engineers ...

PhysicsX

Senior Machine Learning Engineer

New York, NY · On-site

$114K - $157K/yr

  • Retirement

  • PTO

Who We're Looking For As a Senior Machine Learning Engineer in Delivery, you are an experienced ... Own the deployment of ML models and engineering surrogates (e.g., deep learning on CAE/CFD/FEA data ...

PhysicsX

Principal CFD Engineer

New York, NY · On-site

  • Retirement

  • PTO

You're confident setting up CFD simulations independently, interpreting complex results with depth ... This Role In this role, you'll work closely with our Data Scientists, Machine Learning Engineers ...

Neural Concept

Forward Deployed Engineer - US

New York, NY · On-site

$125K - $200K/yr

  • Medical

  • Dental

  • Vision

  • Retirement

  • PTO

You have an excellent understanding of both Engineering and Machine Learning (strict requirement) * You have experience with simulation. Industry experience in CAD / CAE (CFD, FEM, etc) modelling is ...

All JobsMachine Learning Cfd JobsMachine Learning Cfd Jobs in Harrison, NY

Machine Learning Cfd information

See Harrison, NY salary details

$11.7K

$98.8K

$140.1K

How much do machine learning cfd jobs pay per year?

As of Aug 18, 2026, the average yearly pay for machine learning cfd in Harrison, NY is $98,752.00, according to ZipRecruiter salary data. Most workers in this role earn between $90,800.00 and $116,800.00 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 cities near Harrison, NY are hiring for Machine Learning Cfd jobs?

Cities near Harrison, NY with the most Machine Learning Cfd job openings:

Machine Learning Cfd jobs near you
Infographic showing various Machine Learning Cfd job openings in Harrison, NY as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution, with an average salary of $98,752 per year, or $47.5 per hour.