below marketmost similar roles pay hereabove market
This role pays more than
59%
of similar roles. Most pay
$148,650–$214,000
— the blue band above.
At the midpoint, this role pays about
$194k
versus about
$181k
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
496 open roles
on FindRole.
Listed pay typically runs
$172,000–$258,000
across 496 roles with salary data.
The Product Development Engineer joins a team focused on improving the quality and reliability of Server CPUs and Instinct accelerators. This role sits 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 by developing and deploying machine-learning solutions to reduce defective parts per million and optimize test time. Key responsibilities include performing root-cause analysis on yield loss, building analytics within the AVA platform, and driving adaptive binning strategies. You will utilize Python, SQL, pandas, NumPy, and scikit-learn to perform regression, classification, and anomaly detection. The work involves solving complex semiconductor manufacturing problems, specifically correlating test, fab, assembly, and design variables to ensure production-ready reliability.
Identify and prioritize machine learning use cases to improve yield, quality, and manufacturing costs.
Develop and deploy ML solutions for outlier screening, drift detection, and anomaly detection across manufacturing dimensions.
Perform root-cause analysis on yield loss and DPPM drivers by correlating test, fab, assembly, and design variables.
Build and maintain production-ready yield and quality analytics within the AVA analytics platform.
Drive data-driven test, screening, and binning strategies to optimize product quality and manufacturing efficiency.
Author technical documentation and present findings and recommendations to cross-functional teams and executive stakeholders.
Contribute reusable code, analytics frameworks, and best practices to accelerate future development.
What we're looking for
Bachelor’s, Master’s, or Doctoral degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, Applied Math, or a related technical discipline (preferred).
Strong background in semiconductor product development, yield engineering, or test engineering with experience analyzing high-volume manufacturing data (preferred).
Solid foundations in statistics and machine learning, including hypothesis testing, DOE/RSM, regression, classification, and anomaly detection (preferred).
Familiarity with Python and SQL for data analysis and modeling, including pandas, NumPy, and scikit-learn (preferred).
Practical knowledge of semiconductor manufacturing and test flows, including wafer sort, binning strategies, and DPPM analysis (preferred).
Experience with server-class CPUs and/or accelerator/GPU products (preferred).
Demonstrated ability to deploy analytics or ML solutions into production environments (preferred).
ATE
Python
Unix
Windows
Git
Bash
VS Code
SCAN
BIST
SoC
GPU Architecture
x86 Architecture
AI
ML
Hardware Infrastructure
Data Analysis
Semiconductor Manufacturing
Post-Silicon Characterization