Senior Engineering Specialist

4 days ago

Schenectady, New York, United States GE Aerospace Full time
Position Overview
As a key member of the advanced design team, you will play a vital role in the advancement of cutting-edge probabilistic techniques and engineering design solutions, addressing complex real-world challenges in the fields of metamodeling, machine learning, model calibration, validation, uncertainty quantification, optimization, robust design, and inverse modeling, specifically for aerospace applications.

Key Responsibilities

The ideal candidate will engage in the creation of innovative probabilistic and machine learning methodologies to provide exceptional solutions for new product development, service enhancements, energy transition initiatives, and future aviation projects within the aerospace sector. Collaboration with government entities will be essential to tackle significant global issues. You will be part of a diverse team focused on applying prognostics and optimizing systems and structures under uncertainty, considering performance, weight, and cost factors.

Your responsibilities will include:
  • Working closely with design and service teams to develop methodologies for probabilistic design, machine learning, and optimization.
  • Applying these methodologies to real-world industrial scenarios for new product development and service maintenance planning.
  • Integrating probabilistic design, machine learning, and optimization techniques into internal design and service tools.
  • Providing training and mentorship to engineers on probabilistic and machine learning techniques.
  • Leading and overseeing projects, personnel, and funding allocations.
Qualifications / Requirements
  • Doctorate in Mechanical Engineering, Aerospace Engineering, or a related field with a minimum of 3 years of industry experience, or a Master’s degree with at least 8 years of relevant experience.
  • Proven experience in probabilistic design, machine learning, and optimization of engineering systems.
  • Strong foundational knowledge in probabilistic methods, machine learning, Bayesian techniques, and optimization as applied to engineering challenges.
  • Experience in managing government programs and writing proposals.
  • Solid understanding of mechanics and structural analysis tools such as finite element software.
  • Proficiency in developing and utilizing custom software solutions in languages such as Python, C++, Matlab, and others.
  • Legal authorization to work in the U.S. is required.
  • Willingness to work onsite as required.
Preferred Attributes
  • Deep understanding and experience in dynamic Bayesian networks, physics-informed forecasting, time-series analysis, and probabilistic deep learning.
  • Experience in addressing complex engineering challenges using advanced probabilistic and machine learning techniques.
  • Familiarity with mechanical design and analysis methodologies.
  • Experience in software development and fracture mechanics.
  • Demonstrated leadership, communication, and interpersonal skills in a collaborative environment.
  • Strong analytical capabilities and the ability to work effectively across various functions.
  • Ability to perform under pressure and meet project deadlines.
  • Excellent written and verbal communication skills.
Compensation and Benefits
The compensation for this role is competitive and commensurate with experience. Additional benefits include comprehensive healthcare coverage, retirement savings plans, tuition assistance, and various other employee support programs.

This position requires access to sensitive information, and final offers will depend on the ability to obtain necessary authorizations.

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