Machine Learning Engineer

Howmet Aerospace Inc.

(NYSE: HWM), headquartered in Pittsburgh, Pennsylvania, is a leading global provider of advanced engineered solutions for the aerospace and transportation industries.

Our primary businesses focus on jet engine components, aerospace fastening systems, titanium structural parts and forged wheels.

With $7.4 Billion in revenue in 2024, our products play a crucial role in enabling fuel efficiency and lightweighting, contributing to our customers' success and making a positive impact on the world.

To learn more about the way Howmet Aerospace Inc.

is advancing the sustainability of our customers, markets, and communities where we operate, review the 2024 Environmental Social and Governance report at www.howmet.com/esg-report .

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Equal Opportunity Employer:

Howmet is proud to be an Equal Employment Opportunity employer.

We are committed to creating an inclusive environment for all employees.

All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, status as a protected veteran, or other applicable legally protected characteristics.

If you need assistance to complete your application due to a disability, please email TalentAcquisitionCoE_Howmet@howmet.comBasic Qualifications:
• BS degree from an accredited university in Engineering, Data Science, Computer Science, Machine Learning, Materials Science, Mathematics, Statistics, or Analytics.
• Minimum of 2 years of hands-on experience in deep learning and machine learning demonstrating ability to apply advanced statistical methods and machine learning algorithms to production/field data using Python.
• Experience with feature engineering techniques (feature creation, selection, and transformation).
• Employees must be legally authorized to work in the United States.

Verification of employment eligibility will be required at the time of hire.

Visa sponsorship is not available for this position.

Preferred Qualifications:
• Minimum of 5 years of professional experience in data science or machine learning.
• MS or PhD degree from an accredited university in Engineering, Data Science, Computer Science, Machine Learning, Materials Science, Mathematics, Statistics, or Analytics
• Theoretical understanding and practical experience applying reinforcement learning techniques for real time decision making and control.
• Experience using generative models such as diffusion models, VAEs and GANs
• Comprehensive knowledge of advanced analytics and machine learning techniques.
• Strong statistical background with demonstrated expertise in analyzing industrial/manufacturing data.
• Familiarity with manufacturing or industrial plant environments and their unique challenges.
• Knowledge of software development life cycle (SDLC)
• Proficiency in visualization tools (e.g., Power BI)
• Excep...