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.

Build and maintain the V-BAT system reliability model, predicting system-level failure rate using failure-rate data from the field and industry sources.

Create and maintain the V-BAT system fault tree, identifying single points of failure and quantifying their contribution to overall system reliability.

Inform design decisions that eliminate single points of failure and improve the reliability of the system, providing Design-for-Reliability (DfR) guidance in design reviews.

Partner with Design, Fleet Support, Quality, and Manufacturing Engineers on root cause investigations for field failures, and drive corrective and preventive actions to closure.

Drive reliability test campaigns in production and sustainment to verify the system is meeting its reliability requirements and predictions, feeding results back into the model.

Drive production reliability screening campaigns to reduce infant-mortality failures, such as HASS (Highly Accelerated Stress Screening) and ESS (Environmental Stress Screening).

Establish and track reliability metrics — MTBF, failure-rate trends, and reliability growth — and communicate reliability status and risk posture to program leadership.

Staff Engineer, System Reliability (R5533)

Responsibilities

Qualification

Required

Preferred

Benefits

Company

f7d8749a-72d6-407c-bf98-292ea630c73a

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