Senior Staff Product Quality and Reliability Engineer

d-Matrix•Santa Clara, CA

37d•Hybrid

About The Position

At d-Matrix, we are focused on unleashing the potential of generative AI to power the transformation of technology. We are at the forefront of software and hardware innovation, pushing the boundaries of what is possible. Our culture is one of respect and collaboration. We value humility and believe in direct communication. Our team is inclusive, and our differing perspectives allow for better solutions. We are seeking individuals passionate about tackling challenges and are driven by execution. Ready to come find your playground? Together, we can help shape the endless possibilities of AI. Quality and Reliability Engineer establishes and continually refines the robust quality and reliability framework that spans across product and manufacturing processes. This involves embedding quality from design through delivery, making sure every step is optimized to produce reliable, high-performing hardware.

Requirements

A bachelor’s degree in electrical, mechanical, or industrial engineering is the foundational requirement. A master’s degree in a related field is preferred, indicating a desire for deeper theoretical knowledge and advanced problem-solving capabilities.
Candidates should possess 7+ years of experience working with ODM (Original Design Manufacturer) or OEM (Original Equipment Manufacturer) relationships. This experience should ideally be within hardware manufacturing, specifically in the AI and/or high-performance computing sectors.
Manufacturing Process Quality: Knowledge of PCB, PCBA, system assembly, and testing with strong understanding of applying quality engineering principles
Product Development Lifecycles: Understanding the various stages a product goes through from conception to EOL
Quality planning in manufacturing, ensuring no escape from manufacturing (DFQ)
Reliability Prediction: Estimating the likelihood of a product functioning correctly over time
Design for Reliability (DFR): Incorporating reliability considerations from the earliest stages of product design
ORT (Ongoing Reliability Test) / RDT (Reliability Demonstration Test) Development: Designing and implementing tests to assess and confirm product reliability
Statistics related to Quality and Reliability: A robust background in statistical analysis is essential for data-driven decision-making in quality and reliability engineering
Root Cause Analysis: The ability to identify the underlying reasons for process and functional failures, using data from logs, tests, and other sources
Applied Statistics, Reliability modeling, Design of Experiments, Weibull analysis, JMP, Large-Scale Data Analysis, ASQ certifications (CQE/CRE)

Nice To Haves

SQL
Understanding of Linux environment
Python scripting

Responsibilities

Collaborate with Product Development and Design Engineering teams to define critical product quality characteristics and ensure manufacturability and testability are embedded into designs (DFQ)
Establish product-specific quality metrics, test plans, and inspection criteria to ensure adherence to specifications and customer expectations
Drive a comprehensive reliability plan during design, development and mass production phases comprising DFMEAs, reliability predictions (MTBF, MTTR, Availability, AFR)
Develop Reliability Demonstration Tests (RDT, ORT) – resources, infrastructure and test plans in collaboration with Design and hardware operations
Contribute to product qualification tests (structural and environmental tests)
Analyze product performance data from reliability testing, field trials, and early customer feedback to identify trends and drive improvements
Develop, implement, and maintain robust quality control plans and processes
Utilize statistical process control (SPC) and other analytical tools to monitor manufacturing process stability, capability, and performance
Develop IQC, OQC, OBA on products at manufacturers and suppliers
Collaborate with product engineers to drive systematic fixes to issues during NPI, especially for customer-facing issues
Drive stop-ships as needed. Lead teams during major quality events
Conduct comprehensive supplier assessments, audits, and capability for new and existing suppliers. Conduct audits of manufacturing processes and quality systems to ensure compliance with established standards and best practices
Monitor, analyze, and report on key supplier quality performance metrics (e.g., PPM, OTD, SCAR response time, audit scores)
Develop and implement supplier quality agreements, specifications, and quality plans
Partner with Manufacturing Engineering to optimize production processes for quality, ensuring consistent output and defect reduction.
Act as a primary point of contact for analyzing RMA data, field returns, and warranty claims for hardware products
Lead cross-functional teams in deep-dive investigations of returned units, coordinating failure analysis (FA) and identifying root causes
Translate data into actionable insights for design enhancements, manufacturing process improvements, and serviceability
Monitor/communicate key metrics (e.g., return rates, MTBF) and proactively drive initiatives to improve product reliability and customer experience