Influence product power, thermal, and performance definition by connecting architectural goals to measured silicon and system behavior.
Lead the development and evolution of characterization and optimization test plans across diverse usage scenarios.
Drive performance attainment across scale-up and scale-out configurations, including:
Multi-GPU scaling efficiency within a node
Interconnect bandwidth utilization, including XGMI / Infinity Fabric
Collective communication efficiency and communication–compute overlap
Strong- and weak-scaling behavior
Rack- and cluster-level bottleneck identification and mitigation
Analyze interactions among power-management features, thermal behavior, and performance; develop configurations that balance throughput and performance-per-watt.
Identify architectural and system-level bottlenecks, and design experiments that expose and help mitigate worst-case performance scenarios.
Lead prototyping and experimentation to evaluate architectural, firmware, driver, and platform enhancements.
Drive complex root-cause investigations across hardware, firmware, drivers, platform, and workload stacks through to resolution and performance closure.
Serve as a technical authority across teams; communicate findings, tradeoffs, and recommendations to engineering stakeholders.
Mentor engineers and raise the technical quality and consistency of post-silicon performance methodologies, tools, and workflows.
PREFERRED EXPERIENCE
Demonstrated technical leadership on complex, cross-functional engineering programs, including influence across organizations, locations, and time zones.
Strong programming skills, preferably in Python; experience with ML frameworks such as TensorFlow or PyTorch is an advantage.
Proficiency in C/C++ and shell scripting, with experience in performance tooling and automation.
Deep understanding of computer architecture, GPU system organization, and performance analysis.
Extensive knowledge of HPC and ML workloads, including scaling behavior, collective communications, and performance bottlenecks.
Experience analyzing scale-up and scale-out performance at rack or cluster level.
Familiarity with high-speed I/O (HSIO) performance, such as PCIe, is a plus.
Strong analytical judgment and problem-solving skills, with a record of turning ambiguous performance symptoms into evidence-based conclusions and actionable fixes.
Excellent written and verbal communication skills; able to explain complex technical findings and influence engineering decisions.
ACADEMIC CREDENTIALS
Bachelor’s or master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.
LOCATION
Penang, Malaysia
#LI-KL1
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
As a senior technical leader, you will shape post-silicon performance characterization and optimization for AMD Data Center products across single-node, multi-node, and rack-scale deployments. You will set technical direction for complex performance investigations, connect silicon behavior to system-level outcomes, and drive improvements across hardware, firmware, drivers, platforms, and workloads.
This is an individual-contributor role with broad technical influence. You will partner across organizations and sites, mentor engineers, and help translate performance objectives into validated product results.
KEY RESPONSIBILITIES
Define and lead performance-characterization strategies for AMD Data Center products, spanning HPC and ML workloads and single-node through multi-node deployments.
Establish scalable, repeatable workload-execution and performance-data-collection frameworks.
Influence product power, thermal, and performance definition by connecting architectural goals to measured silicon and system behavior.
Lead the development and evolution of characterization and optimization test plans across diverse usage scenarios.
Drive performance attainment across scale-up and scale-out configurations, including:
Multi-GPU scaling efficiency within a node
Interconnect bandwidth utilization, including XGMI / Infinity Fabric
Collective communication efficiency and communication–compute overlap
Strong- and weak-scaling behavior
Rack- and cluster-level bottleneck identification and mitigation
Analyze interactions among power-management features, thermal behavior, and performance; develop configurations that balance throughput and performance-per-watt.
Identify architectural and system-level bottlenecks, and design experiments that expose and help mitigate worst-case performance scenarios.
Lead prototyping and experimentation to evaluate architectural, firmware, driver, and platform enhancements.
Drive complex root-cause investigations across hardware, firmware, drivers, platform, and workload stacks through to resolution and performance closure.
Serve as a technical authority across teams; communicate findings, tradeoffs, and recommendations to engineering stakeholders.
Mentor engineers and raise the technical quality and consistency of post-silicon performance methodologies, tools, and workflows.
PREFERRED EXPERIENCE
Demonstrated technical leadership on complex, cross-functional engineering programs, including influence across organizations, locations, and time zones.
Strong programming skills, preferably in Python; experience with ML frameworks such as TensorFlow or PyTorch is an advantage.
Proficiency in C/C++ and shell scripting, with experience in performance tooling and automation.
Deep understanding of computer architecture, GPU system organization, and performance analysis.
Extensive knowledge of HPC and ML workloads, including scaling behavior, collective communications, and performance bottlenecks.
Experience analyzing scale-up and scale-out performance at rack or cluster level.
Familiarity with high-speed I/O (HSIO) performance, such as PCIe, is a plus.
Strong analytical judgment and problem-solving skills, with a record of turning ambiguous performance symptoms into evidence-based conclusions and actionable fixes.
Excellent written and verbal communication skills; able to explain complex technical findings and influence engineering decisions.
ACADEMIC CREDENTIALS
Bachelor’s or master’s degree in Computer Engineering, Electrical Engineering, Computer Science, or a related field.
LOCATION
Penang, Malaysia
#LI-KL1
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.
