Product Development Engineer

ADVANCE YOUR CAREER. ADVANCE THE WORLD. 

At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies people rely on every day, innovation at AMD is shaping the future. 

Whether you’re designing next-gen processors, enabling AI breakthroughs, or bringing leading edge products to market, every role at AMD contributes to something bigger — technology that moves the world forward. Join us and, together, we’ll advance your career.

THE ROLE:

This role entails improving quality and reliability of AMD’s industry‑leading Server CPUs and Instinct accelerators. This role sits at the intersection of product engineering, test, yield, quality, and data science. You will work hands‑on with massive volumes of manufacturing and test data, transforming them into actionable insights and production‑ready analytics and machine‑learning solutions. You will develop, deploy, and use tools for analyzing test and reliability data, deploy advanced analytics that reduce DPPM (defective parts per million), detect excursions earlier, and optimize test time and cost at scale. This is a highly cross‑functional role where you will partner closely with Product Engineering, Test Engineering, Quality/Reliability, and Operations teams, influencing decisions from early ramp through high‑volume manufacturing. The ideal candidate enjoys moving from exploration to deployment, and communicating results clearly to both technical teams and executive stakeholders.

THE PERSON:

You are a curious, analytical problem solver who thrives in complex, data‑rich environments. You enjoy uncovering patterns in noisy data and translating them into practical improvements that matter in production. You collaborate naturally across functions, influence without authority, and are comfortable balancing deep technical work with clear communication. You are equally effective working independently or as part of a fast‑paced, cross‑disciplinary team, and you take pride in building robust, reusable solutions that scale.

KEY RESPONSIBILITIES:

• Partner with Product Engineering, Test Engineering, Yield Engineering, Quality, and Operations to identify, define, and prioritize analytics and machine‑learning use cases that materially improve yield, quality, and cost.
• Develop and deploy ML/AI solutions for parametric outlier screening, drift detection, and excursion/anomaly detection across wafer, lot, site, and package dimensions.
• Perform in‑depth root‑cause analysis of yield loss and DPPM drivers by correlating test, fab, assembly, and design variables; distinguish systemic issues from statistical noise.
• Build, productionize, and maintain yield and quality analytics within AMD’s AVA analytics platform, moving models from experimentation to scalable deployment.
• Drive adaptive test, screening, and binning strategies using data‑driven insights to optimize product quality and manufacturing efficiency.
• Author clear technical documentation and reports; present findings and recommendations to cross‑functional teams and executive audiences.
• Contribute reusable code, analytics frameworks, and best practices that elevate team capability and accelerate future development.

PREFERRED EXPERIENCE:

• Semiconductor product development, yield engineering, or test engineering, with hands‑on experience analyzing high‑volume manufacturing data.
• Statistics and machine learning, including hypothesis testing, DOE/RSM, regression, classification, outlier detection, time‑series analysis, and anomaly detection.
• Familiarity with Python and SQL for data analysis and modeling (e.g., pandas, NumPy, scikit‑learn), general coding experience and demonstrated past ability in related scientific computing work.
• Practical knowledge of semiconductor manufacturing and test flows, including wafer sort and final test, binning strategies, DPPM analysis, reliability screens, and excursion management.
• Familiarity with yield analytics ecosystems similar to AMD’s environment; experience with server‑class CPUs and/or accelerator/GPU products is highly desirable.
• Demonstrated ability to deploy analytics or ML solutions into production environments, not just develop them in notebooks.

ACADEMIC CREDENTIALS:

• Bachelor’s, Master’s, or Doctoral degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, Applied Math, or a related technical discipline is preferred.

This role is not eligible for visa sponsorship.

#LI-AP1

Benefits offered are described:  AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. 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.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position.  AMD’s “Responsible AI Policy” is available here.

This posting is for an existing vacancy.

THE ROLE:

This role entails improving quality and reliability of AMD’s industry‑leading Server CPUs and Instinct accelerators. This role sits at the intersection of product engineering, test, yield, quality, and data science. You will work hands‑on with massive volumes of manufacturing and test data, transforming them into actionable insights and production‑ready analytics and machine‑learning solutions. You will develop, deploy, and use tools for analyzing test and reliability data, deploy advanced analytics that reduce DPPM (defective parts per million), detect excursions earlier, and optimize test time and cost at scale. This is a highly cross‑functional role where you will partner closely with Product Engineering, Test Engineering, Quality/Reliability, and Operations teams, influencing decisions from early ramp through high‑volume manufacturing. The ideal candidate enjoys moving from exploration to deployment, and communicating results clearly to both technical teams and executive stakeholders.

THE PERSON:

You are a curious, analytical problem solver who thrives in complex, data‑rich environments. You enjoy uncovering patterns in noisy data and translating them into practical improvements that matter in production. You collaborate naturally across functions, influence without authority, and are comfortable balancing deep technical work with clear communication. You are equally effective working independently or as part of a fast‑paced, cross‑disciplinary team, and you take pride in building robust, reusable solutions that scale.

KEY RESPONSIBILITIES:

• Partner with Product Engineering, Test Engineering, Yield Engineering, Quality, and Operations to identify, define, and prioritize analytics and machine‑learning use cases that materially improve yield, quality, and cost.
• Develop and deploy ML/AI solutions for parametric outlier screening, drift detection, and excursion/anomaly detection across wafer, lot, site, and package dimensions.
• Perform in‑depth root‑cause analysis of yield loss and DPPM drivers by correlating test, fab, assembly, and design variables; distinguish systemic issues from statistical noise.
• Build, productionize, and maintain yield and quality analytics within AMD’s AVA analytics platform, moving models from experimentation to scalable deployment.
• Drive adaptive test, screening, and binning strategies using data‑driven insights to optimize product quality and manufacturing efficiency.
• Author clear technical documentation and reports; present findings and recommendations to cross‑functional teams and executive audiences.
• Contribute reusable code, analytics frameworks, and best practices that elevate team capability and accelerate future development.

PREFERRED EXPERIENCE:

• Semiconductor product development, yield engineering, or test engineering, with hands‑on experience analyzing high‑volume manufacturing data.
• Statistics and machine learning, including hypothesis testing, DOE/RSM, regression, classification, outlier detection, time‑series analysis, and anomaly detection.
• Familiarity with Python and SQL for data analysis and modeling (e.g., pandas, NumPy, scikit‑learn), general coding experience and demonstrated past ability in related scientific computing work.
• Practical knowledge of semiconductor manufacturing and test flows, including wafer sort and final test, binning strategies, DPPM analysis, reliability screens, and excursion management.
• Familiarity with yield analytics ecosystems similar to AMD’s environment; experience with server‑class CPUs and/or accelerator/GPU products is highly desirable.
• Demonstrated ability to deploy analytics or ML solutions into production environments, not just develop them in notebooks.

ACADEMIC CREDENTIALS:

• Bachelor’s, Master’s, or Doctoral degree in Electrical Engineering, Computer Engineering, Computer Science, Physics, Applied Math, or a related technical discipline is preferred.

This role is not eligible for visa sponsorship.

#LI-AP1

Benefits offered are described:  AMD benefits at a glance.

AMD does not accept unsolicited resumes from headhunters, recruitment agencies, or fee-based recruitment services. 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.

AMD may use Artificial Intelligence to help screen, assess or select applicants for this position.  AMD’s “Responsible AI Policy” is available here.

This posting is for an existing vacancy.