Principal Product Engineer – AI Cloud & Data Center
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Before you apply
SalaryNo pay range posted
LocationSanta Clara, CA
Typefull-time
SeniorityLead
Experience5–15 yrs
DepartmentNetworking and Compute Product Engineering
Company size10,000+ people
PostedOct 21, 2026 · 2w ago
Verified live3d ago
At a glanceSummarised by Seekless from the posting.
Bachelor’s degree in Computer Science, Electrical Engineering or related fields and 10-15 years of related professional experience
Deep understanding of the end-to-end product lifecycle, with the ability to drive technical decisions that enable scalable productization
Strong expertise in structured problem solving and Root Cause Analysis across silicon, test, and manufacturing environments
Proven ability to translate complex technical data and analytics into clear, executive-level narratives and recommendations
Solid foundation in applied statistics for product characterization, yield improvement, and quality analysis
Working knowledge of data analytics and visualization tools such as JMP and SiliconDash or equivalent platforms
Skills
ATE
93K
Teradyne Tester
JMP
SiliconDash
About Marvell
Marvell’s semiconductor solutions are the essential building blocks of the data infrastructure that connects our world. Across enterprise, cloud and AI, and carrier architectures, our innovative technology is enabling new possibilities.
At Marvell, you can affect the arc of individual lives, lift the trajectory of entire industries, and fuel the transformative potential of tomorrow. For those looking to make their mark on purposeful and enduring innovation, above and beyond fleeting trends, Marvell is a place to thrive, learn, and lead.
Your Team, Your Impact
The Networking and Compute Product Engineering organization at Marvell serves as a core technical leadership function during product development and NPI. The team operates across multiple business units and works closely with design engineering, operations, program management, quality, and leadership to guide technologies from early development into production ready silicon.
Product Engineering is responsible for ensuring technical rigor, manufacturability, and readiness for customer deployment. The function exists to connect architecture, silicon behavior, manufacturing reality, and business constraints, and to drive teams toward the technical decisions required for successful productization.
The organization plays a key role in enabling next-generation compute and AI-driven infrastructure, supporting products deployed at scale across hyperscale data centers and emerging AI workloads.
What You Can Expect
In this role, you will…
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Drive technical leadership from development through production, ensuring decisions support robust, scalable productization
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Serve as a primary technical stakeholder during NPI, guiding teams through characterization, debug, qualification, and readiness discussions
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Align and influence cross‑functional engineering teams toward technically sound, full‑closure solutions during complex problem‑solving efforts
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Define, quantify, and defend product quality, reliability, performance, and cost targets based on data and system‑level impact
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Lead technical risk assessments and tradeoff discussions, driving clarity and direction across engineering, operations, and management
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Represent Product Engineering in customer interactions and internal leadership forums, clearly articulating status, risk, and recommended paths forward
What We’re Looking For
Bachelor’s degree in Computer Science, Electrical Engineering or related fields and 10-15 years of related professional experience. OR Master’s degree and/or PhD in Computer Science, Electrical Engineering or related fields with 5-10 years of experience.
•
Deep understanding of the end‑to‑end product lifecycle, with the ability to drive technical decisions that enable scalable productization
•
Strong expertise in structured problem solving and Root Cause Analysis across silicon, test, and manufacturing environments
•
Proven ability to translate complex technical data and analytics into clear, executive‑level narratives and recommendations
•
Hands‑on experience using ATE for silicon characterization, analysis, and debug; experience with 93K or Teradyne Tester platform is strongly preferred
•
Solid foundation in applied statistics for product characterization, yield improvement, and quality analysis
•
Working knowledge of data analytics and visualization tools such as JMP and SiliconDash or equivalent platforms
•
Strong planning and prioritization skills across multiple parallel efforts; interest in process automation and workflow optimization is a plus