Senior Systems Engineer-DPHM

We are in search of a highly driven DPHM Principal Engineer who possesses both systems engineering and data analytics expertise to become a part of our systems engineering team. This role focuses on developing and managing systems that monitor engine health, predict failures, and enable condition-based maintenance for aero engines. Duties include system design, fault detection, diagnostics, data analysis, and collaboration with engineering teams and customers.

• Define system and subsystem requirements for Prognostics and Health Management (EHM&PHM) systems.
• Use Model-Based Systems Engineering (MBSE) tools to capture requirements and design solutions.
• Advance technologies for gas path diagnostics and engine performance monitoring.
• Develop fault detection and isolation strategies to identify engine issues early.
• Create predictive algorithms that forecast potential failures before they occur.
• Implement condition-based maintenance (CBM) capabilities to reduce downtime and costs.
• Provide diagnostics and prognostics support throughout the engine’s life cycle (from development to in-service engines).
• Process and analyze large data sets to generate health reports, trend analyses, or alerts — to support maintenance decisions for fleets.
• Build diagnostic tools leveraging AI, machine learning, and signal processing.
• Apply tools like MATLAB, Simulink, Python, and Jira for modeling, simulation, and requirements management.
• Work closely with engineering and sustainment teams to ensure PHM systems meet operational needs.
• Partner with engine customers to identify CBM requirements and integrate them into system design.
• Training/mentoring junior engineers to further increase proficiency of systems team.

• Bachelor’s degree in Aerospace, Mechanical or Computer Engineering (or a related STEM field) from an accredited university.
• 10 years of related working experiences (MS count for 2 yrs; PhD for 3yrs)
• Strong background in systems engineering and data analytics.
• Systems Engineering & MBSE:
  Ability to define system/subsystem requirements and capture them using Model-Based Systems Engineering tools.
• Signal Processing & Diagnostics:
  Strong background in analyzing engine data, detecting anomalies, and isolating faults.
• Programming & Tools:
  Proficiency in MATLAB, Simulink, Python, Jira, and other modeling/requirements management tools.
• AI/ML Applications:
  Experience applying machine learning for predictive maintenance and health monitoring.
• US CITIZEN or Green Card Holder.

• Master’s degree or PhD in Engineering (Aerospace, Mechanical, Electrical, or Systems) with specialization in Prognostics and Health Management (PHM)
• 7 years of direct industrial experience in Controls and Diagnostics for gas turbine engines, power generation or aircraft engines
• Excellent communication skills to work with the teams and customers.