At AMD, our mission is to build great products that accelerate next-generation computing experiences—from AI and data centers, to PCs, gaming and embedded systems.
Requirements
- 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
- 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 knowledge of software development methodologies, tools, and processes, including test planning, test design, test execution, and defect management.
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.
Other
- Bachelor’s or Master’s degree in related discipline preferred
- 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
- Strong analytical and problem-solving skills, with an ability to debug and resolve complex issues in software systems.
- AMD benefits at a glance.
