Machine Learning Engineer

RESPONSIBILITIES

Howmet Aerospace is hiring a Machine Learning Engineer with expertise in deep

learning to join our innovative Research and Development team. This role

involves building cutting-edge machine learning and deep learning applications

and collaborating with cross-functional teams to support our casting, alloy,

core, and rings facilities.

The position is located in Whitehall, Michigan in our Howmet Research Center

(HRC).

Primary Responsibilities

* Design, develop, and evaluate advanced deep learning architectures (e.g.,

CNNs, Mask R-CNNs, YOLO) to address complex manufacturing challenges.

* Train and optimize generative models to accelerate development (e.g.,

diffusion models, VAEs, GANs).

* Build and refine machine learning algorithms to enhance Howmet products

across all business units.

* Construct, manipulate, and analyze large datasets using tools such as Python

and SQL.

* Leverage transfer learning techniques and pretrained models to achieve strong

performance with limited data.

* Fine‑tune existing models for specific applications and datasets.

* Develop customized deep learning architectures to handle diverse data types.

* Conduct statistical multi-factor analyses to uncover complex relationships

and improve manufacturing processes.

* Present data-derived conclusions to a non-technical audience.

* Identify opportunities to optimize processes and implement continuous

improvement tools using machine learning.

* Promote a data-driven culture across the organization by expanding machine

learning applications and leading training initiatives.

* Collaborate with internal customers to validate trials, implement process

enhancements, and integrate machine learning into production workflows.

QUALIFICATIONS

Basic

Qualifications

• • MS or PhD 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.
• • This export- control language can be added directly to the job posting in
• the Job Info box of the posting by selecting the sentence in the dropdown field
• titled "Export-Controlled Data" in section 4 of the job requisition

Preferred Qualifications

• • Minimum of 5 years of professional experience in data science or machine
• learning.
• • 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)
• • Exceptional verbal and written communication skills with the ability to
• convey complex ideas clearly.
• • Strong organizational skills and the ability to work independently and in a
• cross-functional team environment.
• Why Join Us?
• • Be at the forefront of innovation, applying machine learning to aerospace
• manufacturing.
• • Collaborate with a supportive, cutting-edge team dedicated to solving
• challenging real-world problems.
• • Access professional growth opportunities and a chance to directly impact
• Howmet Aerospace’s success.
• 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 $8.3 Billion in revenue in 2025, 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 2025 Environmental Social and
• Governance report at www.howmet.com/esg-report
• [https://www.howmet.com/esg-report/]. Follow: LinkedIn
• [https://www.linkedin.com/company/howmet-aerospace], Twitter
• [https://twitter.com/howmetaerospace], Instagram
• [https://www.instagram.com/howmetaerospace/], Facebook
• [https://www.facebook.com/Howmetaerospace/], and YouTube
• [https://www.youtube.com/howmetaerospace].
• 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 [email protected]
• [[email protected]]
• The Howmet engines business produces world-class aerospace engine components,
• including investment castings, fasteners, rings and forgings. Our vacuum melted
• superalloys, machining, performance coatings and hot isostatic pressing for high
• performance parts enable the next generation of quieter, cleaner and more
• fuel-efficient aerospace engines. Able to supply more than 90% of structural and
• rotating aerospace engine components.