BAE Systems is a leading global defense, security, and aerospace company. We deliver a full range of products and services for air, land and naval forces, as well as advanced electronics, information technology solutions, and cyber security. We are experiencing significant growth, driven by innovation and a commitment to supporting our customers. Join us and be a part of something bigger!
We are seeking a motivated and detail-oriented Reliability Engineer to join our dynamic C4ISR (Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance) Systems team. This position offers an excellent opportunity for a recent graduate or early-career professional to gain hands-on experience in a critical engineering discipline, supporting cutting-edge technologies and contributing to national security. You will play a vital role in ensuring the reliability and performance of our systems, working alongside experienced engineers and contributing to continuous improvement. This role is designed for growth, with opportunities to expand your skill set and take on increasing responsibilities as you progress within the company. The BAE Systems C4ISR team develops and supports a diverse portfolio of technologies vital to modern warfare, integrated into platforms like the F-16, F-18, E-2D, and F-35. Our products include: Electronic Warfare Systems: Systems for detecting, jamming, and protecting against electronic threats; Precision Navigation Systems: High-accuracy positioning, navigation, and timing solutions; Advanced Displays & Processing: Ruggedized displays and computing platforms for harsh environments; and Data Links: Secure and reliable data communication networks. We provide the critical command, control, and intelligence capabilities our customers rely on. Failure Analysis & FRACAS (Failure Reporting, Analysis, and Corrective Action System)Analyze failed hardware and software components from production and field returns to determine root cause of failures and assist in developing corrective actions. This includes understanding failure mechanisms and applying engineering principles to diagnose issues.
Collaborate with internal teams (Quality, Hardware Design, Manufacturing, Software Engineering) to gather information, facilitate investigations, and implement solutions.
Interface with Suppliers/Vendors to review their failure analysis findings, ensure alignment, and drive resolution of supplier-related issues.
Perform detailed failure analysis using a variety of techniques (visual inspection, microscopy, component-level testing, data analysis, and potentially more advanced techniques like X-ray or SEM depending on your product).
Author clear, concise, and technically accurate customer-facing failure reports and narratives, including recommended corrective actions and clear communication of technical issues.
Maintain and update the FRACAS database with accurate failure data, analysis results, and corrective action tracking.
Review and interpret data from manufacturing process monitoring, environmental stress screening (ESS), and system testing to identify potential reliability concerns.
Collaborate with test teams to investigate failure modes, refine test procedures, and improve test coverage.
Reliability Data Analysis & Prediction
Collect, analyze, and interpret reliability data from various sources (field failures, testing, simulations) to identify trends, potential areas for improvement, and quantify product reliability.
Utilize statistical tools and techniques (Weibull analysis, MTBF/MTTR calculations, FMECA, Root Cause Analysis, hypothesis testing) to assess system reliability and predict future performance.
Develop and maintain reliability prediction models to assess design margins and optimize product life.
Perform Reliability Growth Analysis to track improvement over time.
Contribute to the development of reliability test plans and strategies.
Maintainability & Testability Analysis
Perform Maintainability analysis, estimate Mean Time To Repair (MTTR), and identify opportunities to improve product serviceability.
Perform system-level testability analysis and demonstrate the effectiveness of diagnostic features.
Support the development and implementation of diagnostic procedures to facilitate efficient troubleshooting.
Process Improvement & Quality Assurance
Identify opportunities to improve manufacturing processes, design practices, and quality control procedures to reduce failure rates and enhance product reliability.
Contribute to the development and implementation of corrective and preventative actions (CAPA).
Participate in Design for Reliability (DFR) and Design for Manufacturability (DFM) reviews.
Lead small-scale reliability improvement projects.
Documentation & Reporting
Create and maintain detailed documentation of failure analysis results, test procedures, reliability data, and analysis reports.
Prepare and deliver presentations summarizing reliability findings for internal stakeholders (engineering teams, management) and potentially external stakeholders (customers, vendors).
Bachelors degree in engineering (Electrical, Mechanical, Aerospace, Systems, or related field) with at least 6 years of experience (4 years with a Masters degree)
Strong analytical and problem-solving skills.
Excellent written and verbal communication skills.
Proficiency in Microsoft Office Suite (Excel, Word, PowerPoint).
Ability to work independently and as part of a team.
Ability to obtain/maintain a security clearance.
Lead reliability science initiatives, including failure analysis, proposal development, and program status management. Proven ability to lead cross-functional teams.
Experience with failure analysis techniques (e.g., visual inspection, microscopy, X-ray, electrical testing).
Familiarity with reliability standards (e.g., MIL-STD-883, MIL-STD-750, MIL-HDBK-217, MIL-STD-1629A, MIL-STD-454, MIL-STD-470, and MIL-HDBK-472).
Knowledge of statistical analysis tools (e.g., Minitab, JMP).
Experience with FRACAS databases and reporting systems, Reliability Testing, Fault Tree Analysis (FTA), and Reliability/Maintainability Modeling including Availability.
Experience with electronic circuits and components.
Understanding of manufacturing processes.
Experience with Python or other scripting languages for data analysis.
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