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 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.