Principal Product Engineer - AI Cloud & Data Center, Platform Transformation Lead

Job Title

Principal Product Engineer - AI Cloud & Data Center, Platform Transformation Lead

Role Summary

Lead product engineering and test strategy for AI, cloud, and data center silicon within Networking and Compute. Own technical decisions from development through NPI to production readiness, focusing on manufacturability, quality, and scalable test economics.

Experience Level

Senior (Principal-level technical leader).

Responsibilities

Lead productization and test strategy across development and manufacturing; influence cross-functional teams to achieve product readiness.

• Provide technical leadership from characterization and debug through qualification and production readiness.
• Define and defend test tier architecture across wafer sort, ATE, and system-level test (SLT).
• Drive ATE-to-SLT correlation, structured escape analysis, and yield learning to inform product/process improvements.
• Evaluate and scale high-throughput SLT approaches, including parallelization and handler/thermal constraints.
• Set and defend product quality, reliability, performance, and cost-of-test targets using data-driven tradeoffs.
• Lead technical risk assessments and cross-functional tradeoff decisions toward clear, actionable outcomes.
• Represent product engineering in customer and leadership forums with clear status, risks, and recommendations.

Requirements

Must-have technical skills and domain experience. Prefer concise, demonstrable experience in volume semiconductor manufacturing and test environments.

• Must-have: Hands-on System Level Test (SLT) platform experience, including SLT board design, DUT fixturing, and socket qualification.
• Must-have: Deep understanding of test tier architecture (wafer sort, ATE, SLT) and experience making tradeoffs on coverage, escape risk, and cost-of-test.
• Must-have: Demonstrated experience driving ATE-to-SLT correlation, escape containment, and yield-learning in a volume manufacturing environment.
• Must-have: Hands-on use of ATE for silicon characterization, analysis, and debug; experience with 93K strongly preferred.
• Must-have: Strong structured problem solving and root cause analysis across silicon, test, and manufacturing.
• Must-have: Applied statistics for product characterization, yield improvement, and quality analysis.
• Must-have: Experience with data analytics and visualization tools such as JMP, SiliconDash, or equivalents.
• Nice-to-have: Experience with automation, workflow optimization, and scaling high-throughput parallel test platforms.
• Nice-to-have: Prior experience supporting hyperscale or AI infrastructure products at volume.

Education Requirements

Bachelor's degree in Electrical Engineering, Computer Engineering, Computer Science, or a related field with 10+ years of relevant industry experience; OR Master's degree or PhD in those fields with 5+ years of relevant industry experience. Related technical degrees are acceptable as stated in the source posting.

About the Company

Company: Marvell Technology

Headquarters: Santa Clara, California, United States

Marvell’s semiconductor solutions serve as essential building blocks of the data infrastructure connecting our world, driving innovation across enterprise, cloud, AI, and carrier architectures. The company focuses on creating transformative technology that shapes the future.