Senior Engineer - Aero Performance & Operability

Queretaro, Mexico

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GE Vernova

The Energy to Change the World. We are GE Vernova. We are helping to accelerate the path to more reliable, affordable, and sustainable energy. With a passion for innovation, we deliver a diverse portfolio of leading technologies we are working...

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Job Description SummaryThe Aeroderivative Performance & Operability Engineering team is a critical pillar within the Aeroderivative Engineering organization, operating at the intersection of engineering, commercial, and digital domains. The team covers project execution and model development for aspects related to performance (thermodynamic cycle models) and operability (including emissions, fuel flexibility, and controls).

This role is focused on developing and owning the NPSS model ecosystem, encompassing the entire lifecycle - method creation , model adjustments, validation, software release, application to both steady state and transient operations. The NPSS ecosystem has portions created and inherited from GEA and this role will create and execute the strategic roadmap for the GEV NPSS ecosystem. The models will be status-matched with field data to ensure real-world accuracy. This is a systems level role that will require collaboration with a multidisciplinary team to ensure we meet the evolving demands of the business and our customers.

Job Description

Roles and Responsibilities

  • Own the Development & Execution of the NPSS Strategic Roadmap: Evaluate the current state and define the future vision for NPSS modeling. Create and execute a strategic roadmap to achieve a best-in-class NPSS ecosystem for steady state, transient, and operability while considering business objectives.
  • Standardize and Improve the Model Development Lifecycle: Drive the process for creation, adjustment, validation, and application of thermodynamic cycle models for Aeroderivative gas turbines using NPSS and associated tools. Ensure that maintenance and interoperability aspects are considered. Create standard work across the team to ensure lean execution.
  • Champion Continuous Improvement: Consistently seek improvements across the modeling lifecycle from methods to data collection to data analysis. Include Python, AI/ML, or other techniques to modernize and automate.  Improve the data reduction process using sound data science techniques.
  • Own the Test Data Integration Lifecycle: Execute on the team’s plan for data improvements in the field and test stand and determine where additional improvements can be made.
  • Technical Leadership: Act as a performance and operability technical expert for Aeroderivative gas turbines, serving as a focal point for coordination with GE Aviation and GE Vernova internal teams.

Required Qualifications

  • This role requires significant experience in the Engineering/Technology & Performance Engineering.
  • Knowledge level is comparable to a Master's degree from an accredited university or college (or Bachelor's degree with relevant experience)

Desired Characteristics

  • Master’s or PhD in engineering or equivalent fields.
  • Significant experience in Aeroderivative performance modeling, particularly in data reduction, status matching, and NPSS cycle model development.
  • Strong programming experience in NPSS, Python, and C.
  • Deep understanding of gas turbine thermodynamics, controls, emissions, and operability.
  • Familiarity with gas turbine performance testing including standards such as ASME PTC 22 or ISO 2314.
  • Understanding of gas turbine combustion and emissions including creation of combustion transfer functions.
  • Experience with fuel flexibility including high hydrogen and its impact on systems such as performance, emissions, operability, and controls.
  • Proficiency in data analysis, data science, and probabilistic modeling.
  • Ability to work effectively in globally distributed teams.
  • Experience in applying continuous improvement methodologies such as Lean to improve operations.
  • Demonstrated ability to think critically and creatively to analyze and resolve complex problems.
  • This position is restricted to Gas Power Engineering internal candidates only

Additional Information

Relocation Assistance Provided: No

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Tags: Data analysis Engineering Machine Learning ML models PhD Python Testing

Region: North America
Country: Mexico

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