This role pays more than
50%
of similar roles. Most pay
$167,375–$241,750
— the shaded band above.
At the midpoint, this role pays about
$194k
versus about
$205k
for comparable roles.
Based on 240 similar postings.
Employer
About Amd
AMD (Advanced Micro Devices) is a semiconductor company that develops high-performance processors, graphics cards, and adaptive computing solutions for gaming, data centers, and embedded markets. Industry: Semiconductors
Amd currently has
367 open roles
on FindRole.
Listed pay typically runs
$166,400–$249,600
across 367 roles with salary data.
As a Senior Staff Product Development Engineer, you will join the team to improve the quality and reliability of Server CPUs and Instinct accelerators. Working at the intersection of product engineering, test, yield, quality, and data science, you will transform massive volumes of manufacturing and test data into actionable insights and production-ready machine-learning solutions. Your daily responsibilities include developing tools for outlier screening, drift detection, and excursion management while building analytics within the AVA platform to optimize test time and cost. You will utilize Python, SQL, pandas, NumPy, and scikit-learn to perform root-cause analysis and develop scalable models. This role addresses critical semiconductor manufacturing challenges by identifying yield loss drivers and implementing data-driven binning strategies to ensure high-quality production for server-class processors and accelerator products in a complex, data-rich environment.
Identify and prioritize machine learning use cases to improve yield, quality, and manufacturing costs.
Develop and deploy ML/AI solutions for outlier screening and anomaly detection across various production dimensions.
Perform root-cause analysis on yield loss and DPPM drivers by correlating test, fab, assembly, and design variables.
Build and maintain scalable yield and quality analytics within the internal AVA platform.
Drive data-driven adaptive test, screening, and binning strategies to optimize manufacturing efficiency.
Create technical documentation and present findings to cross-functional teams and executive audiences.
Develop reusable code and analytics frameworks to improve team capabilities and accelerate development.
What we're looking for
Bachelor's, Master's, or Doctoral degree in Electrical Engineering, Computer Engineering, Computer Science, or a related technical discipline (preferred).
Experience in semiconductor product development, yield engineering, or test engineering with high-volume manufacturing data analysis (preferred).
Proficiency in statistics and machine learning including hypothesis testing, DOE/RSM, regression, and anomaly detection (preferred).
Familiarity with Python and SQL for data analysis and modeling using libraries like pandas, NumPy, and scikit-learn (preferred).
Knowledge of semiconductor manufacturing and test flows, including wafer sort, final test, binning strategies, and DPPM analysis (preferred).
Experience with yield analytics ecosystems and server-class CPUs or accelerator/GPU products (preferred).
Demonstrated ability to deploy analytics or ML solutions into production environments rather than just notebooks (preferred).
Product Engineering
CAD
Six Sigma
Project Management
DOE
Statistical Analysis
Technical Documentation
Design Control
Product Development
Mechanical Engineering
JavaScript
TypeScript
Python
Go
Swift
GenAI
Microservices
SRE
API Design
Distributed Systems
Data Processing
Software Engineering
Automation
Scalability
high-availability