Flight-Hardware Reliability Engineer

Shield AI; Seattle (WA); On-site; USD 140,000 - 210,000; Full time

Job summary

Shield AI is seeking a Hardware Reliability Engineer in Seattle to ensure the robustness and long-term performance of VBAT flight hardware. You will drive design-for-reliability, lead environmental testing, and perform failure analysis across concept to production, collaborating with design, manufacturing, and suppliers.

You will participate in design reviews and FMEA, shape material selection and manufacturing requirements, and use reliability modeling tools to predict system lifespan.

Qualifications

• Materials science and electronics manufacturing fundamentals.
• Experience with reliability concepts and environmental test practices.
• Bachelor or Master-level degrees in relevant fields; advanced degrees preferred.

Responsibilities

• Develop and implement design-for-reliability practices and rigorous testing.
• Lead environmental and stress testing (temperature cycling, vibration, HALT, HASS).
• Perform failure analysis and material characterization; drive root-cause investigations.
• Collaborate with design, manufacturing, and suppliers; participate in design reviews & FMEA.

Skills

Self-starter mindset

Problem-solving

Attention to detail

Team player

Interdisciplinary collaboration

Project management experience

Communication skills

Education

Bachelor's in Materials Engineering

Master's in Materials Engineering or Mechanical/Reliability Engineering

Tools

Python

NumPy

Pandas

SciPy

Plotly

Matplotlib

Job description

Shield AI is seeking a Hardware Reliability Engineer in Seattle to ensure the robustness and long-term performance of VBAT flight hardware. You will drive design-for-reliability, lead environmental testing, and perform failure analysis across concept to production, collaborating with design, manufacturing, and suppliers.

You will participate in design reviews and FMEA, shape material selection and manufacturing requirements, and use reliability modeling tools to predict system lifespan.