Sr. Staff Power Performance Architect

Reposted 18 Days Ago
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Santa Clara, CA, USA
Hybrid
165K-265K Annually
Senior level
Artificial Intelligence • Machine Learning • Software
The Role
Responsible for power estimation, architectural tool development for AI workloads, and optimizing performance monitoring in micro-architecture and RTL. Collaborate with teams for design integration and silicon validation.
Summary Generated by Built In

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. 

Role Overview

d-Matrix is looking for a Senior Staff Power Performance Architect to own pre-silicon power estimation across our next-generation AI accelerators. In this role, you will drive both RTL-level and physical-design-level power estimation, and build an architectural power estimation tool that models power from system configuration and die-level metrics for AI workloads. You will partner closely with front-end architects, DV engineers, and backend design teams to identify power activity windows, define performance monitoring requirements, and translate that analysis into hardware capability improvements and die-level design changes. This role also contributes directly to micro-architecture and RTL design, verification, and silicon bring-up, making it central to how d-Matrix balances performance and power efficiency at the silicon level.

What You Will Do
  • Own pre-silicon power estimation for design blocks, spanning both RTL-level and physical-design-level estimation.

  • Partner with front-end and DV engineers to identify power activity windows, and work with the RTL team to implement estimation feedback and optimize power.

  • Build an architectural power estimation tool for AI workloads that computes power from system configuration and die-level metrics, including workload profiling based on memory size, bandwidth, and gate counts of compute/memory blocks.

  • Collaborate with frontend architects and backend design to define performance monitor availability, system requirements, and usage, then drive that analysis into hardware capability improvements and die-level design modifications.

  • Lead micro-architecture and RTL design, synthesis, and logic/physical power-performance verification using leading-edge CAD tools and semiconductor process technologies.

  • Design and implement performance-enabling and power-saving/monitoring functions that support efficient design, test, and debug, and participate in silicon bring-up and validation.

What You Will Bring
  • 8+ years of relevant experience in IC power/performance architecture, RTL, or physical design, with a Master's degree in Electrical Engineering, Computer Engineering, or Computer Science.

  • Solid understanding of power, performance, micro-architecture, RTL, and physical design in the context of digital system and IC design, including the full IC design flow (Arch → uarch → RTL → Schematic → Layout → Verification → Fabrication → HVM).

  • Familiarity with at least one EDA tool for power estimation.

  • Ability to move fluidly between RTL, physical design, and automation, including building script utilities to improve design execution productivity across the design team.

  • Programming proficiency in TCL and Python, with experience using libraries, APIs, data parsing, and algorithmic thinking.

  • Self-motivated with a fast, iterative approach to design work, sound engineering judgment, and a bias toward action.

Preferred Qualifications
  • Exposure to power estimation and performance metrics such as TDP, PMAX, EDP, Peak, and Average.

  • Familiarity with power/frequency scaling techniques (DFS, DVFS, AFS, AVFS).

  • Familiarity with power delivery network (PDN) analysis, including resonance, impedance (Z(f)), and voltage droop analysis.

Equal Opportunity Employment Policy

d-Matrix is proud to be an equal opportunity workplace and affirmative action employer. We’re committed to fostering an inclusive environment where everyone feels welcomed and empowered to do their best work. We hire the best talent for our teams, regardless of race, religion, color, age, disability, sex, gender identity, sexual orientation, ancestry, genetic information, marital status, national origin, political affiliation, or veteran status. Our focus is on hiring teammates with humble expertise, kindness, dedication and a willingness to embrace challenges and learn together every day.

d-Matrix does not accept resumes or candidate submissions from external agencies. We appreciate the interest and effort of recruitment firms, but we kindly request that individual interested in opportunities with d-Matrix apply directly through our official channels. This approach allows us to streamline our hiring processes and maintain a consistent and fair evaluation of al applicants. Thank you for your understanding and cooperation.

Skills Required

  • Master's degree in electrical engineering, Computer Engineering or Computer Science
  • 10 - 15 years industry experience or equivalent
  • Understanding of Power, Performance, micro-architecture, RTL, and Physical design
  • Good understanding of ASIC design flow
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The Company
HQ: Santa Clara, CA
102 Employees

What We Do

d-Matrix is building a new way of doing datacenter AI inferencing using in-memory computing (IMC) techniques with chiplet level scale-out interconnects. Founded in 2019, d-Matrix has attacked the physics of memory-compute integration using innovative circuit techniques, ML tools, software and algorithms; solving the memory-compute integration problem, which is the final frontier in AI compute efficiency.

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