CPU Core Physical Design Methodology Staff Engineer

Advanced Micro Devices; Austin (TX); On-site; USD 190,000 - 230,000; Full time

Job summary

Advanced Micro Devices in Austin, TX is seeking a Physical Design Methodology Staff Engineer to serve as the technical backbone of our high‑performance core team. You will move beyond standard implementation to optimize the EDA tool‑chain and drive GHz‑class silicon.

You will own automation, scripting (Tcl/Python), and flow development to improve PPA, design predictability, and tape‑outs, working with best‑in‑class partners and internal teams.

Qualifications

• MS or PhD in Electrical or Computer Engineering or equivalent industry experience.
• Expertise with physical design toolchains and flow automation.
• Experience optimizing PPA through tool-level tuning and scripting.

Responsibilities

• Flow Architecture: end‑to‑end physical implementation flows prioritizing scalability and QoR.
• EDA Tool Optimization: interface with vendors to drive adoption and troubleshoot tool behavior.
• Methodology Development: automate design space exploration and ECO implementation.
• PPA Optimization: tune placement, routing, CTS to meet frequency/power targets.
• Signoff Integration: build automated signoff loops for reliable tapeouts.
• Constraint Engineering: develop complex SDC constraints aligned with intent.
• Data‑Driven Analysis: analyze metrics across iterations to improve methodology.

Skills

EDA tool mastery

Scripting Tcl/Python

Flow customization

QoR tuning

Clocking & CTS

Education

MS/PhD in EE/CE

Tools

Synopsys Fusion Compiler/ICC2

Cadence Innovus

Job description

WHAT YOU DO AT AMD CHANGES EVERYTHING

At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond.

THE ROLE

We are seeking a Physical Design Methodology Staff Engineer to serve as the technical backbone of our high‑performance core team. In this role, you will move beyond standard implementation to focus on the "how" of physical design. You will own the optimization of our EDA tool‑chain, developing and refining the methodologies that enable our CPU cores to hit aggressive PPA (Power, Performance, and Area) targets. You will act as a power‑user and flow‑architect, bridging the gap between raw EDA tool capabilities and the complex requirements of GHz‑class silicon.

THE PERSON

You are an EDA‑centric engineer who views the design flow as a system to be tuned, automated, and perfected. You are not just a user of tools; you are an expert in how tool algorithms, constraints, and physical parameters interact to produce optimal silicon. If you are driven by the challenge of reducing turnaround time, improving design predictability, and pushing EDA tools to their absolute limits, you are the ideal candidate for this role.

KEY RESPONSIBILITIES

• Flow Architecture: Design, implement, and maintain end‑to‑end physical implementation flows (Synthesis through Signoff) that prioritize scalability, reproducibility, and high QoR.
• EDA Tool Optimization: Act as the primary interface with EDA vendors to drive tool adoption, evaluate new features, and troubleshoot complex tool‑behavior issues.
• Methodology Development: Develop and deploy advanced scripting frameworks (Tcl/Python) to automate design space exploration, ECO implementation, and multi‑corner timing closure.
• PPA Optimization: Systematically analyze and tune tool settings—including placement density, routing congestion management, and clock tree synthesis (CTS) strategies—to meet aggressive frequency and power targets.
• Signoff Integration: Build and refine automated signoff loops (STA, IR/EM, Physical Verification) to ensure high‑confidence tape‑outs with minimal iterations.
• Constraint Engineering: Develop and validate complex SDC constraints, ensuring that tool‑driven optimizations are aligned with architectural intent and physical realities.
• Data‑Driven Analysis: Utilize big‑data approaches to analyze design metrics across multiple iterations, identifying trends in tool performance and implementing corrective methodology improvements.

Preferred Experience – EDA & Methodology Expertise

• Tool Mastery: Expert‑level proficiency in industry‑standard physical design platforms (e.g., Synopsys Fusion Compiler/ICC2, Cadence Innovus).
• Scripting & Automation: Advanced Tcl/Python/Perl skills; proven ability to build custom tool wrappers, automated debug utilities, and flow‑management scripts.
• Flow Customization: Experience in customizing tool‑specific APIs to handle unique design challenges, such as custom cell integration or non‑standard floorplanning requirements.
• QoR Tuning: Demonstrated success in "tuning the engine"—adjusting tool‑specific switches, constraints, and optimization strategies to resolve timing, power, or congestion bottlenecks.

Preferred Experience – Technical Depth

• Advanced Node Implementation: Deep understanding of the physical effects at 7nm/5nm/3nm nodes and how to configure EDA tools to mitigate parasitic, crosstalk, and LDE (Layout Dependent Effect) issues.
• Signoff Methodology: Mastery of the signoff ecosystem (PrimeTime SI, RedHawk‑SC, Voltus, Calibre); experience in building "push‑button" signoff flows that minimize manual intervention.
• Clocking & Power Flows: Expertise in configuring advanced CTS methodologies and power‑aware implementation flows (e.g., UPF/CPF‑driven design, multi‑Vt optimization).
• Constraint Management: Deep knowledge of MMMC (Multi‑Mode Multi‑Corner) environments and the ability to manage complex timing exceptions in high‑frequency CPU designs.

Academic Credentials

• MS or PhD in Electrical Engineering, Computer Engineering, or a related field (or equivalent industry experience).

Location

Austin, TX

Visa Eligibility

This role is not eligible for visa sponsorship.

Equity

AMD and its subsidiaries are equal opportunity, inclusive employers and will consider all applicants without regard to age, ancestry, color, marital status, medical condition, mental or physical disability, national origin, race, religion, political and/or third‑party affiliation, sex, pregnancy, sexual orientation, gender identity, military or veteran status, or any other characteristic protected by law. We encourage applications from all qualified candidates and will accommodate applicants’ needs under the respective laws throughout all stages of the recruitment and selection process.