Senior Manager, Silicon Speed Productization

NVIDIA's Silicon Co-Design Group (SCG) leads silicon programs from first power-on to high-volume production. We're hiring a Senior Manager to lead our Silicon Speed Productization team, focusing on simulation-to-silicon speed correlation and ensuring products meet intended frequencies across various conditions.

Responsibilities:

• Close the prediction-to-silicon loop: Own speed characterization and correlation from pre-silicon planning to production sign-off across GPU, CPU, and SoC programs
• Resolve speed failures: Drive root-cause closure for frequency corners, minimum operating voltage, critical paths, and workload behavior divergences
• Define product limits: Refine methodologies for silicon margining, process-voltage-temperature characterization, guardbanding, aging, and speed binning
• Left-shift learning: Feed measured-silicon insights back into timing models, critical-path predictions, test content, design practices, and future architectures
• Give leadership clarity: Convert characterization data into decision-ready options for leadership
• Scale analysis and coverage: Build closed-loop data, automation, and AI-assisted workflows for test orchestration, anomaly detection, and reporting
• Build the organization: Hire, develop, and retain a high-performing, globally-distributed team

Requirements:

• BS, MS, or PhD in Electrical Engineering, Computer Engineering, Systems Engineering (or equivalent experience)
• 12+ years of experience in silicon characterization, post-silicon validation, timing or performance analysis, including 5+ years leading technical teams
• Proven management experience developing senior engineers and first-line managers
• Deep technical foundation in digital design, computer architecture, static timing analysis, and semiconductor process variation
• Hands-on expertise with silicon speed characterization, simulation-to-silicon correlation, and process-voltage-temperature dependencies
• Demonstrated ability to drive ambiguous issues to root-cause closure
• Proficiency with data-analysis and automation tools like Python, JMP, SQL
• Strong written and verbal communication skills

Nice to have:

• Evidence of tracing a frequency miss to a specific critical path or process corner and driving a productized fix
• Experience building reusable correlation or characterization methodologies
• Applied AI tools to characterization or debug workflows
• Comfort navigating ambiguity and aligning global teams