PD Engineer, Annapurna Labs

Salary: $136,000 - 157,800 per year Requirements: We require a bachelors degree in Electrical Engineering or a related discipline. We need experience with block design using EDA tools such as Cadence, Mentor Graphics, Synopsys, or similar platforms. We expect hands-on knowledge across synthesis, equivalency verification, floor planning, bus/pin planning, place and route, power and clock distribution, congestion analysis, timing closure, IR drop analysis, physical verification, and ECO. We require a strong understanding of sign-off activities, including timing, IR/EM, and physical verification. Preferred qualifications include expertise with CAD tools to build flows for synthesis, formal verification, floor planning, bus/pin planning, place and route, power and clock distribution, congestion analysis, timing closure, IR drop analysis, physical verification, and ECO. We value 4+ years of experience integrating IP and the ability to define and drive IP requirements in the physical domain. We prefer experience extracting design parameters, QoR metrics, and trend analysis. We look for candidates who meet or exceed our leadership principles and functional/technical depth requirements for the role. Responsibilities: We lead block physical implementation through synthesis, floor planning, bus/pin planning, place and route, power and clock distribution, congestion analysis, timing closure, IR drop analysis, physical verification, ECO, and sign-off. We develop cloud infrastructure that supports physical design work. We improve RTL-to-GDS flows and methodology to strengthen PPA and turnaround time. We build dashboards and central reporting tools to track projects and visualize QoR and statistics. We work directly with RTL, Package Design, DFT, and other teams to refine methodologies, improve efficiency, and drive issues to resolution. We partner with EDA tool vendors to evaluate new tools, resolve defects, and improve usability. Technologies: AWS Cloud Hardware Machine Learning DevOps Support More: We are part of the Cloud-Scale Machine Learning Acceleration team, focused on designing and optimizing hardware in our data centers, including technologies such as AWS Inferentia, our machine learning inference product built for high performance at low cost. This is a fast-paced, intellectually demanding role where we work alongside thought leaders across multiple technology areas and continuously push to improve performance, quality, and cost. We offer an inclusive culture, comprehensive benefits including health coverage, 401(k) matching, paid time off, parental leave, sign-on payments, and RSUs, with base pay listed for Cupertino, CA and Austin, TX. The role is associated with Amazon and includes opportunities to make a meaningful impact on large-scale deployments and customer experience. last updated 37 week of 2026