Reliability Manager, Strategy na Wing

About The Role

Wing is looking for a Reliability Manager to join and lead critical functions within our Hardware Reliability team. This role is based onsite in Palo Alto, CA. This role is responsible for defining and maturing the Design for Reliability (DFR) and Data Science programs across our fleet of automated delivery aircraft. You will act as the key leader, driving organizational excellence, translating complex mission profiles into actionable test and data strategies, and partnering across engineering, manufacturing, and operations to ensure the resilience, safety, and operational excellence of our hardware in harsh, dynamic environments.

Key Responsibilities

• Define and own the overall reliability and validation strategy, partnering with design engineering to integrate Design-for-Reliability (DFR) principle early in the product lifecycle.
• Drive reliability simulations (thermal, vibration, fatigue, lifecycle stress) and physics-of-failure-based reliability models early in design to inform trade-offs and prevent costly late-stage redesigns.
• Define and maintain reliability requirements and metrics at all system levels, translating mission profiles (e.g., aircraft delivery cycles, environmental stress) into accelerated life test plans (HALT, HASS, ORT).
• Develop Reliability Block Diagrams and Allocation Models, FMECA, and support test-to-failure experiments to uncover design weaknesses.
• Lead the interface with Quality and Manufacturing teams to align on product qualification requirements for Suppliers and Contract Manufacturers (CMs). You will drive reliability qualification and ongoing monitoring of CMs, defining and implementing supplier reliability requirements (DFR, test coverage, accelerated life tests) during sourcing and vendor onboarding, and managing complex qualification programs.
• Collaborate cross-functionally with Operations, Manufacturing, and Supply Quality Engineering (SQE) to implement Corrective and Preventive Actions (CAPA) for production escapes and supply chain incidents.
• Own and mature the Reliability Data Science program, building and maintaining the data pipeline for collecting reliability data from tests, manufacturing, and field fleet operations.
• Automate dashboards, metrics, and Anomaly Detection to monitor field performance, applying advanced methods like survival analysis, Weibull modeling, and Bayesian methods to forecast lifetime and failure rates.
• Correlate field incidents with design, manufacturing, and supplier-level data to quantify reliability risk for key business and product decisions, and show how reliability trends affect fleet uptime, safety, and cost to drive continuous DFR/DFX improvements.

Minimum Qualifications

• 8+ years of experience in hardware reliability engineering, design, and failure analysis, with a focus on electronic and mechatronic systems in harsh environments (aerospace/automotive preferred).
• 2+ years of experience defining and leading high-impact, cross-functional technical programs or managing engineering teams, demonstrating strong strategic execution.
• Bachelor's degree in a directly related field or equivalent practical experience.
• Extensive, hands-on experience with reliability engineering principles, including accelerated life modeling, fatigue prediction, FMEA, component derating, and testing (HALT/HASS, vibration, thermal cycling).
• Deep expertise in reliability data science—including building data pipelines, applying statistical analysis (Weibull, survival), and translating complex data into clear business and engineering insights.
• Proficiency in a programming language (preferably Python) to write and modify scripts for test automation and data analysis.
• Demonstrated ability to partner with Quality and Manufacturing teams to embed reliability requirements and controls into the supply chain and production processes.
• Exceptional written and verbal communication skills to influence technical and non-technical executives and stakeholders, ensuring the adoption of technical recommendations and strategic plans
• Experience managing geographically dispersed teams or cross-functional stakeholders.
• Knowledge of regulatory standards pertaining to drone or aviation reliability and safety.
• Experience with advanced ML/AI approaches for predictive maintenance and failure forecasting.