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Machine Learning Cfd Jobs in Spokane, WA (NOW HIRING)

Metallurgical Engineer

Spokane, WA · On-site

$85K - $150K/yr

Experience with the advanced computing technologies and algorithms, such as machine learning, to ... FEA and CFD tools. * An ability to apply continuous improvement tools and methodologies to ...

Metallurgical Engineer

Spokane, WA · On-site

$85K - $150K/yr

Experience with the advanced computing technologies and algorithms, such as machine learning, to ... FEA and CFD tools. * An ability to apply continuous improvement tools and methodologies to ...

Metallurgical Engineer

Spokane, WA · On-site

$85K - $150K/yr

Experience with the advanced computing technologies and algorithms, such as machine learning, to ... FEA and CFD tools. * An ability to apply continuous improvement tools and methodologies to ...

Machine Learning Cfd information

See Spokane, WA salary details

$11.1K

$94K

$133.5K

How much do machine learning cfd jobs pay per year?

As of Aug 6, 2026, the average yearly pay for machine learning cfd in Spokane, WA is $94,049.00, according to ZipRecruiter salary data. Most workers in this role earn between $86,400.00 and $111,200.00 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 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 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 are popular job titles related to Machine Learning Cfd jobs in Spokane, WA? For Machine Learning Cfd jobs in Spokane, WA, the most frequently searched job titles are:
What cities near Spokane, WA are hiring for Machine Learning Cfd jobs? Cities near Spokane, WA with the most Machine Learning Cfd job openings:
Infographic showing various Machine Learning Cfd job openings in Spokane, WA 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 $94,049 per year, or $45.2 per hour.

Metallurgical Engineer

Kaiser Aluminum

Spokane, WA • On-site

$85K - $150K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 29 days ago


Kaiser Aluminum rating

7.4

Company rating: 7.4 out of 10

Based on 30 frontline employees who took The Breakroom Quiz

294th of 536 rated manufacturers


Job description

Kaiser Aluminum is known around the world for its superior quality. Our secret is what we put into it-innovative thinking, industry-leading reliability, and a world-class commitment to customer service. In short, the same qualities we look for in our people. We are looking for a Metallurgical Data Scientist to join the Kaiser Aluminum onsite team in Spokane Washington with a background in aluminum manufacturing, physical/mechanical metallurgy and Finite Element Analysis!
Must be a USA person (identified as US Citizen, US Permanent Resident (Green Card), any individual who is granted status as a "protected person" under 8 U.S.C. 1324b(a)(3).
Benefits
  • Salary range $85,000 to $150,000 commensurate with experience.
  • High deductible medical, dental, vision, and basic life insurance, including spouse and children (modest payroll deductions).
  • 10 paid holidays per year.
  • Vacation (3 weeks starting out).
  • Supplemental leave (used in conjunction with Washington Paid Family & Medical Leave).
  • 401K with matching company funds.
  • Quarterly bonus structure.
  • Tuition reimbursement.

The Metallurgical/Data Scientist is responsible for analysis, design, testing and implementation of existing and new applications and integrations. The ideal candidate will be a strong technical resource with the ability to understand, learn and master many different diverse technologies used across the enterprise, work with minimal supervision, and has ability to work closely with the business and technical resources.
What you will work on:
  • Conduct the low cost and high quality product and process improvement and optimization through the combination of advanced data analytics and ICME (Integrated Computational Material Science).
  • Monitor, evaluate, and apply the advanced computing technologies and algorithms for the most sophistic data analytics to uncover insights and hidden variables, identify root causes and patterns, forecast outcomes, and provide data-drive solutions.
  • Production process data collection, high dimension large dataset multivariate analysis, classic and penalized regression predictive modelling, advanced neural-network and decision-tree based predictive modeling development and applications.
  • Develop general and challenge specific predictive modeling capabilities by using commercially available software and/or internal computational codes.
  • Design and development of alloys and processes for Aluminum products through advanced data analytics and ICME.
  • Provide guidance and mentorship supports for different levels of data analytics including the principle and limits of different analytical algorithms.
  • Provide support for Industry 4.0 initiatives.
  • Develop, define, and complete on-time assigned research & development chartered projects.
  • Support plant projects as directed.
  • Write technical reports summarizing work as well as presentations to peers on progress at continuous improvement meetings.
  • Perform metallurgical and structural analysis of aluminum products.
  • Work in cross-functional teams to develop process and production improvements.
  • 5S of assigned areas.

What you will bring to the role:
  • MS degree in Data Science, or Computational Material Science, or Statistics, or Material Science or Mechanical Engineering is required. A PhD is preferred.
  • Excellent experience in statistical analysis and computing for data-driven problem solving in manufacturing environment.
  • Strong skills and experience in predictive modeling development by using multivariate analysis, classic and penalized regression predictive modelling, advanced neural-network and decision-tree based predictive modeling technologies.
  • Experience with the advanced computing technologies and algorithms, such as machine learning, to build high quality predictive modes, uncover insights and hidden variables, and provide solutions.
  • Experience in large dataset collection, integration, and visualization by using Excel, SQL, Mintab, Python, etc.
  • Background in aluminum manufacturing, physical, and mechanical metallurgy.
  • Experience in thermodynamic and kinetic material modeling by using CALPHA principle, and process simulations by using FEA and CFD tools.
  • An ability to apply continuous improvement tools and methodologies to processes and projects
  • Excellent communication skills (written and verbal) and organizational skills.
  • Proven ability to work in teams.
  • Ability to manage multiple tasks simultaneously.

PREFERRED SKILLS
  • Experience in metal rolling process simulation through FEA, Crystal Plasticity (CP) model, and other microstructure-based material models.
  • Experience in material characterization such as microstructure and mechanical properties.

WORK ENVIRONMENT
  • Approximately 70% of the job function is performed in an office setting requiring normal safety precautions. 30% of the job function is required in the plant. There is exposure to operating machinery and a manufacturing environment.

We are an equal opportunity employer. All applicants will be considered based on job-related qualifications and abilities. There shall be no discrimination on the basis of age, race, color, religion, sex, sexual orientation, gender identity, gender expression, national origin, veteran, or disability status.
About Kaiser Aluminum: Talented people join our team because we are a company passionate about environmental sustainability, employee growth, contributing back to our communities and championing an inclusive culture.
No third-party candidate submissions are being accepted at this time for this opening

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