Machine Learning Systems Validation Engineer

WHAT YOU DO AT AMD CHANGES EVERYTHING 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. Grounded in a culture of innovation and collaboration, we believe real progress comes from bold ideas, human ingenuity and a shared passion to create something extraordinary. When you join AMD, you’ll discover the real differentiator is our culture. We push the limits of innovation to solve the world’s most important challenges—striving for execution excellence, while being direct, humble, collaborative, and inclusive of diverse perspectives. Join us as we shape the future of AI and beyond. Together, we advance your career. We’re looking for an engineer to help ensure the quality, performance, and scalability of modern machine learning workloads running on AMD GPUs and the ROCm software stack. In this role, you will design, implement, and execute validation strategies focused on modern AI models and frameworks, including large language models, diffusion models, and other deep learning architectures across multiple GPU platforms. You will collaborate closely with developers, performance engineers, and infrastructure teams to validate training, fine-tuning, and inference workflows, investigate issues, and help ship high-quality releases that meet our correctness, conformance, and performance goals. What you’ll do: Develop and maintain automated and manual tests for machine learning workloads. Run ML training and inference pipelines across various GPU platforms and environments and analyze results. Investigate failures, identify clear steps to reproduce issues, and collaborate with developers to resolve them. Help improve validation coverage for modern ML frameworks and emerging AI model architectures. Support release qualification and contribute to improving test reliability, coverage, and validation processes. What we’re looking for: Hands-on experience and knowledge of AI model training, fine-tuning, and inference using popular frameworks, as well as their performance optimization. Strong experience with machine learning frameworks such as PyTorch, TensorFlow, ONNX Runtime, JAX, or similar. Familiarity with modern AI model architectures such as LLMs, diffusion models and vision models. Proficiency in scripting languages such as Python, Bash, or PowerShell. Experience with OS SDKs and developer tools in both Linux and Windows environments. 3+ years of relevant experience Nice to have: Experience with distributed and multi-node training workflows, including familiarity with reinforcement learning approaches such as RL and RLHF. Experience with model optimization, quantization, or inference acceleration. Exposure to GPU programming or compute frameworks such as CUDA, HIP, or OpenCL. Understanding of software quality assurance processes and open-source software. Success looks like Increased automated coverage and fewer manual steps. Reliable test runs with fast feedback. Clear, actionable bug reports and faster resolution of issues. Stable releases across different systems and GPU generations. Why join Work on high-impact software used by developers and researchers worldwide. Collaborate with experienced teams across software, tools, and hardware. Opportunity to shape test strategy and automation at scale. Preferred Experience BS/MS in Computer Engineering, Computer Science, or a related field. #LI-CM1 #LI-HYBRID 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.

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.

We’re looking for an engineer to help ensure the quality, performance, and scalability of modern machine learning workloads running on AMD GPUs and the ROCm software stack. In this role, you will design, implement, and execute validation strategies focused on modern AI models and frameworks, including large language models, diffusion models, and other deep learning architectures across multiple GPU platforms. You will collaborate closely with developers, performance engineers, and infrastructure teams to validate training, fine-tuning, and inference workflows, investigate issues, and help ship high-quality releases that meet our correctness, conformance, and performance goals. What you’ll do: Develop and maintain automated and manual tests for machine learning workloads. Run ML training and inference pipelines across various GPU platforms and environments and analyze results. Investigate failures, identify clear steps to reproduce issues, and collaborate with developers to resolve them. Help improve validation coverage for modern ML frameworks and emerging AI model architectures. Support release qualification and contribute to improving test reliability, coverage, and validation processes. What we’re looking for: Hands-on experience and knowledge of AI model training, fine-tuning, and inference using popular frameworks, as well as their performance optimization. Strong experience with machine learning frameworks such as PyTorch, TensorFlow, ONNX Runtime, JAX, or similar. Familiarity with modern AI model architectures such as LLMs, diffusion models and vision models. Proficiency in scripting languages such as Python, Bash, or PowerShell. Experience with OS SDKs and developer tools in both Linux and Windows environments. 3+ years of relevant experience Nice to have: Experience with distributed and multi-node training workflows, including familiarity with reinforcement learning approaches such as RL and RLHF. Experience with model optimization, quantization, or inference acceleration. Exposure to GPU programming or compute frameworks such as CUDA, HIP, or OpenCL. Understanding of software quality assurance processes and open-source software. Success looks like Increased automated coverage and fewer manual steps. Reliable test runs with fast feedback. Clear, actionable bug reports and faster resolution of issues. Stable releases across different systems and GPU generations. Why join Work on high-impact software used by developers and researchers worldwide. Collaborate with experienced teams across software, tools, and hardware. Opportunity to shape test strategy and automation at scale. Preferred Experience BS/MS in Computer Engineering, Computer Science, or a related field. #LI-CM1 #LI-HYBRID