AMD · 12 hours ago
Principal Software Quality Engineer – GPU & Machine Learning
San Jose, CA
Full-time
Hybrid
Lead/Staff
$200K/yr - $300K/yrAMD is a company focused on building products that accelerate next-generation computing experiences. The Principal Software Quality Engineer will drive the end-to-end delivery of software solutions for machine learning models, collaborating with various teams to optimize and implement testing strategies for GPU-based software products.
Embedded SoftwareArtificial Intelligence (AI)SemiconductorCloud ComputingElectronicsHardwareAI InfrastructureComputerEmbedded SystemsGPU
No H1B
Responsibilities
Develop and implement the overall QA strategy and frameworks for testing GPU-based software products, spanning various hardware and software configurations
Evaluate and improve existing QA methodologies, tools, and processes and best practices, including automation tools, testing methodologies, test configuration management, and performance testing techniques
Collaborate with software developers, program managers, QA teams, and other stakeholders to incorporate their feedback into test strategy and design
Define cataloging methods for test plans, test suites, and test cases that cover functional and non-functional requirements
Analyze and debug complex failure scenarios in GPU software environment, including root cause analysis and implementation of corrective actions
Establish and monitor metrics to assess the efficiency and effectiveness of the Software development process, utilizing data-driven insights to drive continuous improvement
Provide training and mentorship to QA engineers and other stakeholders on best practices, testing methodologies, and tools used in the QA process
Stay current with the latest trends and technologies in the Compute domain to ensure the implementation of best practices and cutting-edge testing methodologies
Aware of industry standards and regulations, including ISO, IEEE, and other relevant standards
Qualification
Required
Develop and implement the overall QA strategy and frameworks for testing GPU-based software products, spanning various hardware and software configurations
Evaluate and improve existing QA methodologies, tools, and processes and best practices, including automation tools, testing methodologies, test configuration management, and performance testing techniques
Collaborate with software developers, program managers, QA teams, and other stakeholders to incorporate their feedback into test strategy and design
Define cataloging methods for test plans, test suites, and test cases that cover functional and non-functional requirements
Analyze and debug complex failure scenarios in GPU software environment, including root cause analysis and implementation of corrective actions
Establish and monitor metrics to assess the efficiency and effectiveness of the Software development process, utilizing data-driven insights to drive continuous improvement
Provide training and mentorship to QA engineers and other stakeholders on best practices, testing methodologies, and tools used in the QA process
Stay current with the latest trends and technologies in the Compute domain to ensure the implementation of best practices and cutting-edge testing methodologies
Aware of industry standards and regulations, including ISO, IEEE, and other relevant standards
You are a subject matter expert and strong technical contributor with machine learning and GPU programming experience
You excel as part of a team where communication and team skills are highly valued
Preferred
Relevant experience in Machine Learning and/or GPU programming
Experience in deep learning frameworks (e.g. TensorFlow, Keras, PyTorch, Caffe, ONNX, etc) and familiarity with CNN/LSTM model architectures
Knowledge of CPU and GPU architecture, and experience in GPGPU programming technologies
Proven experience in a SW or QA Architect or Senior Technical Engineer role
Strong knowledge of software development methodologies, tools, and processes, including test planning, test design, test execution, and defect management
Expertise in embedded software process, systems architecture and GPU technologies, including programming skills, such as C, C++ and Python
Familiarity with various GPU hardware platforms and wide variety of operating systems (Linux and Windows) variants
Experience with automated testing tools as well as experience in Continuous Integration and Continuous Deployment (CI/CD) pipelines process
Strong analytical and problem-solving skills, with an ability to debug and resolve complex issues in software systems
Excellent communication, collaboration skills, with the ability to effectively work with cross-functional teams and diverse stakeholders
Led or played key role in QA teams' transformations to agile development and validation methods
Master's degree in related discipline or previous experience are preferred
Benefits
AMD benefits at a glance.
Company
AMD
Advanced Micro Devices is a semiconductor company that designs and develops graphics units, processors, and media solutions.
Founded in 1969
10001+ employees
Funding
Current Stage
Public CompanyTotal Funding
unknownKey Investors
OpenAIDaniel Loeb
2025-10-06Post Ipo Equity
2023-03-02Post Ipo Equity
2021-06-29Post Ipo Equity
Leadership Team
Lisa Su
Chair & CEO
Mark Papermaster
CTO and EVP
Recent News
2026-02-06
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2026-02-06
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