AMD is looking for a senior software engineer to join our growing team. As a key contributor you will be part of a leading team to drive and enhance AMD’s abilities to deliver the highest quality, industry-leading technologies to market.
Key Responsibilities:
Design, implement, and maintain CD/CI pipelines that automate build, test, and deployment workflows for GPU-accelerated features and libraries.
Develop and maintain automated test frameworks, regression suites, and validation tools for functional, performance, and stability testing.
Create and manage test and training environments (on-prem and cloud), including lab orchestration, provisioning, and configuration management for boards, systems, and test agents.
Integrate test automation with code repositories, build systems, artifact stores, and reporting tools to provide timely feedback to developers.
Collaborate with software engineers to translate test requirements into automated test cases and to integrate ML and shader workloads into CD/CI pipelines.
Implement monitoring, logging, and alerting to track test runs, lab health, and test coverage; diagnose and remediate infrastructure or automation failures.
Support bring-up and validation of new hardware platforms through automated tests and lab setups.
Develop scripts and utilities to automate repetitive lab tasks (e.g., board swaps, system setups, firmware flashing, test data collection).
Provide training, documentation, and support to development teams on using the CD/CI systems, test environments, and best practices.
Execute and prioritize tasks assigned by senior staff and management; participate in postmortems and continuous improvement of testing processes.
requirements-expected :
Preferred Experience:
Experience designing, implementing, and operating CD/CI systems (Jenkins, GitLab CI, Azure DevOps, CircleCI, or similar).
Strong scripting and automation skills (Python, Bash/PowerShell, or similar) and experience with lab orchestration tools (Ansible, Terraform, Kubernetes, etc.).
Familiarity with test automation frameworks and test result reporting (pytest, GoogleTest, Allure, TestRail, etc.).
Experience with Windows and Linux based build/test environments and knowledge of system-level scripting and tooling.
Practical understanding of GPU-accelerated workloads, real-time graphics workflows, or ML inference pipelines; exposure to shader code (HLSL) or GPU programming is a plus.
Experience interfacing automation with hardware test beds: board management, firmware flashing, serial logs, power control, and remote access systems.
Familiarity with performance and stability testing methodologies, and tools for profiling and diagnosing crashes/TDRs.
Strong debugging, troubleshooting, and root-cause analysis skills across hardware, drivers, and user-space software.
Excellent written and verbal communication skills; ability to produce clear documentation and train distributed teams.
Comfortable working within geographically distributed teams and coordinating across business units.
Academic Credentials:
Bachelor’s or Master’s degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent practical experience.
