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Machine Learning Cfd Jobs (NOW HIRING)

Gates

Product Development AI Engineer

Englewood, CO · On-site

$115K - $125K/yr

Apply machine learning techniques to predict product performance, durability, and failure modes ... Integrate AI models with engineering tools such as CAD/CAE, FEA, CFD, PLM, and test lab systems.

JetZero

Senior Aerodynamics Design Engineer

Long Beach, CA · On-site

$195K - $220K/yr

Conduct CFD simulations to assess aerodynamic performance under various conditions. * Develop ... Hands-on experience with optimization techniques (DOE, adjoint methods, machine learning-assisted ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

... CFD tools, meshing software, and CAD platforms for multiphysics simulations; contribute to ... machine learning and AI solutions--such as surrogate modeling and physics-informed neural networks ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

... CFD tools, meshing software, and CAD platforms for multiphysics simulations; contribute to ... machine learning and AI solutions--such as surrogate modeling and physics-informed neural networks ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

... CFD tools, meshing software, and CAD platforms for multiphysics simulations; contribute to ... machine learning and AI solutions--such as surrogate modeling and physics-informed neural networks ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA

$145K - $175K/yr

Strong C++ software engineering skills and experience applying machine learning (ML) and AI to ... Develop and optimize next-generation software that integrates CFD tools, meshing software, and CAD ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA

$145K - $175K/yr

Strong C++ software engineering skills and experience applying machine learning (ML) and AI to ... Develop and optimize next-generation software that integrates CFD tools, meshing software, and CAD ...

SpaceX

Software Engineer, Simulation

Hawthorne, CA · On-site

$145K - $175K/yr

Strong C++ software engineering skills and experience applying machine learning (ML) and AI to ... Develop and optimize next-generation software that integrates CFD tools, meshing software, and CAD ...

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Machine Learning Cfd information

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How much do machine learning cfd jobs pay per year?

As of Jun 1, 2026, the average yearly pay for machine learning cfd in the United States is $93,015.00, according to ZipRecruiter salary data. Most workers in this role earn between $85,500.00 and $110,000.00 per year, depending on experience, location, and employer.

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.

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 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.

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.

More about Machine Learning Cfd jobs
What cities are hiring for Machine Learning Cfd jobs? Cities with the most Machine Learning Cfd job openings:
What states have the most Machine Learning Cfd jobs? States with the most job openings for Machine Learning Cfd jobs include:
What job categories do people searching Machine Learning Cfd jobs look for? The top searched job categories for Machine Learning Cfd jobs are:
Machine Learning Cfd jobs near you
Infographic showing various Machine Learning Cfd job openings in the United States as of May 2026, with employment types broken down into 85% Full Time, 10% Part Time, and 5% Temporary. Highlights an 87% Physical, 8% Hybrid, and 5% Remote job distribution, with an average salary of $93,015 per year, or $44.7 per hour.
Product Development AI Engineer

Product Development AI Engineer

Gates Corporation

Englewood, CO

Other

Medical, Dental, Vision, Retirement, PTO

Posted 11 days ago

Gates Corporation rating

6.4

Company rating: 6.4 out of 10

Based on 9 frontline employees who took The Breakroom Quiz

356th of 415 rated machine equipment manufacturers

Job description

Are you inspired by challenging the status quo? Do you thrive in collaborative environments that drive results? If so, Gates could be for you.

Gates is a leading manufacturer of application-specific fluid power and power transmission solutions. We push the boundaries of material science to engineer solutions that continually exceed customer expectations.

Let's simplify it, think belts and hoses. Found in motorcycles, conveyor belts, cars, tractors, blenders, vacuum cleaners, bicycles, & 3D printers just to name a few. Because why not do it all?

Position Summary

Gates Corporation is seeking a Product Development AI Engineer to accelerate innovation across our global product portfolio by applying artificial intelligence, machine learning, and advanced analytics to engineering and product development processes.

This role will work at the intersection of engineering, data, and digital technology, partnering with product development teams and GPLM to improve design efficiency, predictive performance modeling, materials optimization, testing automation, and lifecycle management for Gates' power transmission and fluid power products.

The ideal candidate combines strong AI/ML expertise with an understanding of engineering systems, physical products, and industrial workflows, enabling Gates to move faster from concept to commercialization while improving product performance, reliability, and quality.

Essential Duties and Responsibilities

AI-Driven Product Development

  • Design, develop, and deploy AI/ML models to support product design, simulation, testing, and validation activities.
  • Apply machine learning techniques to predict product performance, durability, and failure modes using historical test, field, and simulation data.
  • Develop AI-enabled tools for design optimization, including automated parameter tuning, materials selection, and geometry optimization.

Engineering & Domain Integration

  • Collaborate closely with fluid power and power transmission team, mechanical, materials team, and manufacturing engineers to embed AI solutions into existing product development workflows.
  • Integrate AI models with engineering tools such as CAD/CAE, FEA, CFD, PLM, and test lab systems.
  • Translate complex physical engineering problems into data-driven and AI-compatible formulations.

Advanced Analytics & Data Engineering

  • Curate, clean, and structure large datasets from test labs, manufacturing systems, field data, and supplier data.
  • Develop data pipelines and feature engineering approaches suitable for industrial-scale ML applications.
  • Ensure models are explainable, validated, and usable by nondatascience engineering teams.

Digital Transformation & Innovation

  • Contribute to Gates' digital product development roadmap, identifying opportunities where AI can deliver measurable business value.
  • Prototype and industrialize AI solutions that reduce development cycle time, improve first-pass yield, and lower cost of poor quality.
  • Partner with IT, Digital, and Cybersecurity teams to ensure scalable, secure deployment.

Governance & Best Practices

  • Apply best practices for model lifecycle management, versioning, validation, and documentation.
  • Support responsible AI use, including transparency, robustness, and compliance with Gates' engineering and quality standards.
  • Mentor engineers and developers on AI concepts and tools within the product development organization.
Requirements and Preferred Skills
  • Bachelors in Math, Computer Science, Data Science, Mechanical Engineering, Electrical Engineering, Materials Science, or a related field.  Degrees at the Master or PhD level are preferred.Experience
  • 5-7+ years of experience applying machine learning or advanced analytics in an engineering, manufacturing, or industrial context
  • Demonstrated experience supporting physical product development (as opposed to pure digital products)
  • Hands-on experience working with engineering datasets (test data, sensor data, simulation results)

Technical Skills

  • Strong proficiency in Python and common ML libraries (e.g., TensorFlow, PyTorch, scikit-learn)
  • Experience with data analysis, feature engineering, and model evaluation
  • Familiarity with engineering tools and environments (e.g., CAD/CAE, PLM systems, test automation, industrial databases)
  • Working knowledge of statistics, optimization techniques, and numerical methods

Preferred Qualifications

  • Experience in industrial equipment, or advanced manufacturing
  • Exposure to physics-informed machine learning, digital twins, or hybrid physics/AI models
  • Experience deploying AI solutions in production or regulated engineering environments
  • Understanding of materials behavior, tribology, fatigue, thermal systems, or fluid dynamics
  • Experience working in Agile or hybrid product development environments

Key Competencies

  • Strong problem-solving skills with a system-level mindset
  • Ability to translate between engineering domain experts and data/AI practitioners
  • Clear technical communication and documentation skills
  • Curiosity, pragmatism, and a results-driven approach to innovation

PAY & BENEFITS

    • Full-Time
    • Salary: $115,000-$125,000
    • Medical, Dental, Vision insurance and other voluntary benefit options: benefits begin on the first day of the month immediately following your date of hire
    • Eligible for 3 weeks of paid vacation + 11 holidays (9 scheduled & 2 floating) + 8 sick days. All vacation days are accrued
    • 401(k): 3% company contribution and additional 3% company match
    • Tuition Reimbursement

WHY GATES?

Founded in 1911 in Denver, Colorado, Gates is publicly traded on the NYSE. While we might operate in a vast amount of time zones we operate as 'One Gates' and have a common goal of pushing the boundaries of materials science. We invest in our people, bringing real-world experience that enables us to solve our customers' diverse challenges of today and anticipate those of tomorrow.

WORK ENVIRONMENT

Gates is an Equal Opportunity and is committed to ensuring equal employment opportunities for all job applicants and employees. Employment decisions are based upon job-related reasons regardless of race, sex, color, religion, age, disability, pregnancy, citizenship, sexual orientation, gender identity, national origin, protected veteran status, genetic information, marital status, or any other consideration defined by law.

While performing the duties of this job, the employee is frequently required to sit; use hands and fingers to work with objects, tools, or controls; and use office equipment including computers, telephones, and/or copiers/scanners. The employee must frequently lift and/or move up to 10 pounds.  

For individuals assigned and/or hired to work in Colorado, Gates is required by law to include a reasonable estimate of the compensation for this role. This compensation range is specific to the State of Colorado and takes into account various factors that are considered in making compensation decisions, including but not limited to the candidate's relevant experience, qualifications, skills, competencies, and proficiency for the role.


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