Shield AI
Staff Engineer, System Reliability (R5533)
Dallas, TX · On-site · Mid
- Discipline
- Systems
- Industry
- Defense
Spec sheet
Automatically summarized from the employer’s posting. Check the original description below for full requirements.
V-BAT Division
Reliability Modeling Engineer to own the reliability model and failure-prediction strategy for unmanned aircraft systems, translating field data and test results into models that inform design, production, and sustainment decisions.
Required
- reliability modeling
- failure-prediction
- design for reliability
- data-driven decision making
- cross-functional collaboration
- fleet support
- test results integration
- field data analysis
Preferred
- experience with unmanned systems
- Aircraft reliability
- modeling in reliability software
- quantitative risk assessment
- Sustainment and design-for-reliability collaboration
Employer description
Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems. Its products include Hivemind autonomy software, V-BAT and X-BAT aircraft, and Aechelon simulation and synthetic reality technologies. With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide. For more information, visit www.shield.ai. Follow Shield AI on LinkedIn, X, Instagram, and YouTube.
Job Description:
Shield AI is looking for a Reliability Modeling Engineer to own the reliability model and failure-prediction strategy for the V-BAT unmanned aircraft system. In this role you will build the quantitative backbone that predicts how the system fails, why it fails, and how to design those failures out — translating field data, industry sources, and test results into models that directly inform design, production, and sustainment decisions. You will be the reliability subject-matter expert who partners across Design, Manufacturing, Quality, and Fleet Support to drive measurable improvements in system reliability.
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