Northrop Grumman Aeronautics Systems has an opening for an Engineer / Principal Systems Engineer - Prognostics (PHM) position to join our team of qualified, diverse individuals in Melbourne, Florida. This position is fully onsite with no remote work available.
You should have a background in Health Management (HM), with a particular focus on Prognostics and Diagnostic processes, analysis, and design for integrated systems. You should also have a strong foundational understanding of Reliability and Maintainability (R&M) engineering analyses and processes.
This position requires proven experience integrating inputs from multiple systems to generate an integrated architecture; identify, develop, and decompose requirements; developing simple and complex logic or rulesets which can be used in Prognostic and Diagnostic Algorithms; and analyze flight and sensor logs for anomalous behavior and identifying root cause to reduce troubleshooting and increase fault isolation. Analyses are performed at all stages of the complete system lifecycle to include: concept, design, fabrication, test, installation, operation, maintenance and disposal. Candidate will be expected to perform Built in Test (BIT) analysis, timeline analyses, detailed trade studies, sensor placement assessments, Mission Systems software analyses, and interface definition studies to translate customer requirements into hardware and software specifications.
Performs technical planning, system integration, verification and validation, cost and risk, and supportability and effectiveness analyses for total systems. Analyses are performed at all levels of total system product to include: concept, design, fabrication, test, installation, operation, maintenance and disposal. Ensures the logical and systematic conversion of customer or product requirements into total systems solutions that acknowledge technical, schedule, and cost constraints. Performs functional analysis, timeline analysis, detailed trade studies, requirements allocation and interface definition studies to translate customer requirements into hardware and software specifications.
Job Duties:
Analyze various types of flight/fault logs, assign Fault Identification (FID) codes, and host customer BIT Review Boards (BRB)
Coordinate with stakeholders, suppliers, and customers, internally and externally, in support of improving Built-In-Test (BIT) Fault Detection, Fault Isolation and BIT False Alarm performance metrics
Develop models and scalable algorithms derived from both data and underlying physics of failure models to evaluate the condition of Mission and Air Vehicle systems
Create predictive models of physical degradation, failures, and data-driven prognostics algorithms to assess the health and performance of critical components
Formulate health monitoring strategies to detect anomalies/outliers in real flight data
Conduct research and development projects concentrating on Prognostic Health Management (PHM) and Condition Based Maintenance Plus (CBM+)
Gather and analyze component and WRA failure history, including failure modes, downtime, MTBF, power cycles, reboots, repeat faults, etc.
Effectively communicate and present to project and program management, and other technical and non-technical managers and customers
Work collaboratively in a team environment with other highly motivated system engineers and data scientists
The individual we seek will be self-motivated, proactive, goal-oriented to help us grow our services, become even better at what we do and will possess the following qualifications.
**This requisition may be filled at either a Engineer Level or a Principal Level**
Basic Qualifications Engineer:
Bachelor’s Degree in a Science, Technology, Engineering, or Mathematics (STEM) field from an accredited university with 2 years previous experience working in an Engineering or Technical position OR a Master’s Degree in STEM with 0 years of relevant experience.
Experience within Health Management, Prognostics, Diagnostics, and/or Reliability & Maintainability Engineering disciplines
Previous experience, including academic research, directly related to the development of Prognostics Health Management (PHM) or Condition Based Maintenance Plus (CBM+) technologies, or analysis and simulation of complex electrical or mechanical systems
Working knowledge in data analysis (algorithms, data structures, and architectures), probability, statistics, signal processing, and predictive modeling
Experience with anomaly/outlier detection in time series data
Current in-scope (within 6 years) U.S. Government Secret Clearance as well as the ability to obtain Program Special access within a reasonable period of time, as determined by the company to meet its business needs.
Basic Qualifications Principal Engineer:
Bachelor’s Degree in a Science, Technology, Engineering, or Mathematics (STEM) field from an accredited university with 5 years previous experience working in an Engineering or Technical position OR a Master’s Degree in STEM with 3 years of relevant experience OR a PhD in STEM with 1 years of relevant experience.
Experience within Health Management, Prognostics, Diagnostics, and/or Reliability & Maintainability Engineering disciplines
Previous experience, including academic research, directly related to the development of Prognostics Health Management (PHM) or Condition Based Maintenance Plus (CBM+) technologies, or analysis and simulation of complex electrical or mechanical systems
Working knowledge in data analysis (algorithms, data structures, and architectures), probability, statistics, signal processing, and predictive modeling
Work experience with anomaly/outlier detection in time series data
Current in-scope (within 6 years) U.S. Government Secret Clearance as well as the ability to obtain Program Special access within a reasonable period of time, as determined by the company to meet its business needs.
Preferred Qualifications:
Master’s degree in a STEM field (Mechanical, Electrical or Manufacturing).
Active U.S. Government Top Secret Clearance.
Programming skills, preferably in Python and its numerical and data libraries (pandas, scipy, numpy, etc.)
Proficiency in Microsoft Visio, Project, Word, PowerPoint, and Excel Office Products
Work experience with big data tools (Databricks, Presto, Data Lake, Apache Spark, etc.)
Work experience developing visualization tools and dashboards using Tableau
Familiarity with fault detection and diagnosis methods, and reliability analysis
Experience with MLOps and building machine learning pipelines in a professional setting
Demonstrated history of generating new ideas or improving existing ideas in statistical modeling or machine learning, indicated by accomplishments such as first-author publications or projects
Experience with data architectures in relation to how to store, fetch, and manipulate data (SQL, custom APIs, etc.)