Whoop
NPI Quality Engineer (Hardware)
$120K–$160K
Boston, MA · On-site · Full-time · Posted Oct 13, 2026
- Experience
- 3–5+ years; experience supporting hardware products through one or more phases of development, validation, manufacturing readiness, and/or launch.
- Education
- Bachelor’s degree in Mechanical Engineering, Electrical Engineering, Manufacturing Engineering, Industrial Engineering, Quality Engineering, or a related technical discipline.
- Visa sponsorship
- Participates in E-Verify to determine employment eligibility.
About the job
Supports product quality for hardware programs from development through validation, manufacturing readiness, and launch, helping identify and resolve product and process risks.
What you'll do
- Support quality planning, risk management, validation, and launch-readiness activities, including DFMEA, CTQ definition, and reliability planning.
- Analyze engineering and manufacturing data; support root-cause analysis and corrective and preventive actions for product and process issues.
- Work with engineering, supplier, operations, and manufacturing partners to track quality issues, assess risks, and improve product quality processes.
What they ask for
- Bachelor’s degree in a relevant engineering or technical discipline.
- 3–5+ years of experience in Product Quality, NPI Quality, Manufacturing Quality, Product Engineering, or related engineering roles supporting complex hardware.
- Experience supporting hardware product development, validation, manufacturing readiness, and/or launch.
- Working knowledge of quality methodologies including DFMEA, PFMEA, CTQ, DOE, SPC, MSA, GR&R, root-cause analysis, CAPA/8D, and statistical quality methods.
Nice to have
- Experience with suppliers or manufacturing partners, preferably in high-volume manufacturing.
- Experience in consumer electronics, wearables, medical devices, or similarly complex hardware.
Pay
$120,000 - $160,000 USD base salary
Tools
DFMEA, PFMEA, CTQ, DOE, SPC, MSA, GR&R, CAPA/8D
AI focus
Strong commitment to embracing and leveraging AI tools in day-to-day tasks, ensuring AI-assisted work meets the same quality standards as personal contributions.
Model-written summary · the original posting is authoritative