Machine Learning Engineer at Howmet Aerospace

Posted in General Business 22 days ago.

Type: Full-Time
Location: Whitehall, Michigan





Job Description:

About Howmet Aerospace

Howmet Aerospace Inc. (NYSE: HWM), headquartered in Pittsburgh, Pennsylvania, is a leading global provider of advanced engineered solutions for the aerospace and transportation industries. The Company's sales for 2022 approximated $5.7 billion. The Company's primary businesses focus on jet engine components, aerospace fastening systems, titanium structural parts and forged wheels. With nearly 1,150 granted and pending patents, the Company's differentiated technologies promote more fuel efficiency for aircraft and commercial transportation. For more information, visit www.howmet.com , including content shared during the Company's May 2022 Technology Day.

Follow: LinkedIn , Twitter , Instagram , Facebook , and YouTube .

Howmet is proud to be an Equal Employment Opportunity and Affirmative Action employer. We celebrate diversity and 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.comMinimum Qualifications:


  • A MS or PhD Degree from an accredited university in Data Science, Computer Science, Computer Engineering, Mathematics, Statistics, Analytics, or related.

  • Minimum of 2 years of experience in advanced data science or machine learning required.

  • Demonstrated success applying advanced statistical methods and machine learning algorithms to production/field data using Python or R.

  • 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:

  • 5 years of professional data science or machine learning experience.

  • Manufacturing / industrial plant experience

  • Experience in applying advanced data and statistical analysis methods to industrial manufacturing data.

  • Visualization tools: Power BI, Tableau

  • Engineering data tools: SQL, SAS, Minitab, JMP, MS Excel, Six Sigma

  • In depth knowledge of advanced analytic and machine learning techniques.

  • Strong verbal and written communication skills. Excellent analytical skills.

  • Ability to work in a self-directed AND cross-functional team environment.

  • Strong organizational skills.

Minimum Qualifications:

  • A MS or PhD Degree from an accredited university in Data Science, Computer Science, Computer Engineering, Mathematics, Statistics, Analytics, or related.

  • Minimum of 2 years of experience in advanced data science or machine learning required.

  • Demonstrated success applying advanced statistical methods and machine learning algorithms to production/field data using Python or R.

  • 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:

  • 5+ years of professional data science or machine learning experience.

  • Manufacturing / industrial plant experience

  • Experience in applying advanced data and statistical analysis methods to industrial manufacturing data.

  • Visualization tools: Power BI, Tableau

  • Engineering data tools: SQL, SAS, Minitab, JMP, MS Excel, Six Sigma

  • In depth knowledge of advanced analytic and machine learning techniques.

  • Strong verbal and written communication skills. Excellent analytical skills.

  • Ability to work in a self-directed AND cross-functional team environment.

  • Strong organizational skills.

Howmet Aerospace is hiring a Machine Learning Engineer for our Research and Development group. This position involves working in a close cross-functional team environment supporting Howmet's casting, alloy, core, and rings facilities.

Primary Responsibilities:


  • Evaluating, developing, and testing Artificial Intelligence / Machine Learning applications and solutions.

  • Developing and optimizing machine learning algorithms for Howmet products across all businesses.

  • Constructing and manipulating large datasets using tools such as Python, R, SAS, SQL, Minitab, PowerBI and more, to extract multi-factor and complex interactions to drive improvements in manufacturing.

  • Solving operational, quality, and engineering problems using big data and image sets.

  • Identifying opportunities and deploying tools to drive continuous improvement using machine learning.

  • Driving a data-driven culture across the organization through expanding applications and training.

  • Interacting with internal customers to drive validation trials, implement process improvements, and integrate machine learning into current production.

Howmet Aerospace is hiring a Machine Learning Engineer for our Research and Development group. This position involves working in a close cross-functional team environment supporting Howmet's casting, alloy, core, and rings facilities.

Primary Responsibilities:


  • Evaluating, developing, and testing Artificial Intelligence / Machine Learning applications and solutions.

  • Developing and optimizing machine learning algorithms for Howmet products across all businesses.

  • Constructing and manipulating large datasets using tools such as Python, R, SAS, SQL, Minitab, PowerBI and more, to extract multi-factor and complex interactions to drive improvements in manufacturing.

  • Solving operational, quality, and engineering problems using big data and image sets.

  • Identifying opportunities and deploying tools to drive continuous improvement using machine learning.

  • Driving a data-driven culture across the organization through expanding applications and training.

  • Interacting with internal customers to drive validation trials, implement process improvements, and integrate machine learning into current production.





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