AMD
Senior Technical Validation Engineer – AI/ML & GPU Performance QA
This range is provided by AMD. Your actual pay will be based on your skills and experience — talk with your recruiter to learn more.
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.
Together, we advance your career.
Key Responsibilities
Lead validation for ML/AI models: accuracy testing, performance benchmarking, regression, drift detection, A/B testing
Test ML frameworks: PyTorch, Hugging Face, MLFlow experiment tracking
Validate wide varieties of AI models to ensure correctness in distributed training or inference
Perform GPU testing & profiling: ROCm/CUDA validation, performance profiling, memory/thermal analysis, multi-GPU scaling
Validate HPC frameworks, distributed runtimes, compilers, and GPU libraries
Build scalable CI/CD workflows for ML/HPC validation. Develop automated test pipelines using Docker, Kubernetes, GitHub Actions, Jenkins
Validate cloud-based AI workloads on AWS SageMaker, Lambda, and S3
Test benchmarks under containerized and virtualized GPU environments
Design and implement automated validation pipelines for ML frameworks across GPU platforms
Develop and maintain benchmarking suites for AI models and HPC workloads, focusing on performance, scalability, and regression detection
Multi-node validation efforts using orchestration tools to simulate real-world distributed training and inference
Collaborate with hardware and software teams to validate GPU hardware platforms for ML and HPC readiness
Analyze performance metrics using profiling tools and provide actionable insights
Drive test content development for emerging AI workloads, including LLMs, vision models, and scientific computing benchmarks
Perform bottleneck analysis, hyperparameter validation, and competitive benchmarking
Mentor junior engineers and contribute to validation strategy, tooling, and best practices
Preferred Experience
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field
8+ years of experience in validation engineering, ML infrastructure, or HPC performance testing
Strong hands‑on experience with GPU platforms (NVIDIA CUDA, AMD ROCm) and their software ecosystems
Deep understanding of AI model architectures, training/inference workflows, and ML performance bottlenecks
Proven experience with CI/CD systems, Git, Docker, and automated test frameworks
Expertise in multi-node orchestration and distributed system validation
Familiarity with HPC benchmarks (HPL, HPCG, MLPerf) and AI model benchmarking methodologies
Proficiency in scripting and automation (Python, Bash, YAML) in Linux environments
Strong communication, documentation, and cross-functional collaboration skills
Benefits Benefits offered are described: AMD benefits at a glance.
Equal Opportunity Statement 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.
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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.
Together, we advance your career.
Key Responsibilities
Lead validation for ML/AI models: accuracy testing, performance benchmarking, regression, drift detection, A/B testing
Test ML frameworks: PyTorch, Hugging Face, MLFlow experiment tracking
Validate wide varieties of AI models to ensure correctness in distributed training or inference
Perform GPU testing & profiling: ROCm/CUDA validation, performance profiling, memory/thermal analysis, multi-GPU scaling
Validate HPC frameworks, distributed runtimes, compilers, and GPU libraries
Build scalable CI/CD workflows for ML/HPC validation. Develop automated test pipelines using Docker, Kubernetes, GitHub Actions, Jenkins
Validate cloud-based AI workloads on AWS SageMaker, Lambda, and S3
Test benchmarks under containerized and virtualized GPU environments
Design and implement automated validation pipelines for ML frameworks across GPU platforms
Develop and maintain benchmarking suites for AI models and HPC workloads, focusing on performance, scalability, and regression detection
Multi-node validation efforts using orchestration tools to simulate real-world distributed training and inference
Collaborate with hardware and software teams to validate GPU hardware platforms for ML and HPC readiness
Analyze performance metrics using profiling tools and provide actionable insights
Drive test content development for emerging AI workloads, including LLMs, vision models, and scientific computing benchmarks
Perform bottleneck analysis, hyperparameter validation, and competitive benchmarking
Mentor junior engineers and contribute to validation strategy, tooling, and best practices
Preferred Experience
Bachelor’s or Master’s degree in Computer Science, Electrical Engineering, or related field
8+ years of experience in validation engineering, ML infrastructure, or HPC performance testing
Strong hands‑on experience with GPU platforms (NVIDIA CUDA, AMD ROCm) and their software ecosystems
Deep understanding of AI model architectures, training/inference workflows, and ML performance bottlenecks
Proven experience with CI/CD systems, Git, Docker, and automated test frameworks
Expertise in multi-node orchestration and distributed system validation
Familiarity with HPC benchmarks (HPL, HPCG, MLPerf) and AI model benchmarking methodologies
Proficiency in scripting and automation (Python, Bash, YAML) in Linux environments
Strong communication, documentation, and cross-functional collaboration skills
Benefits Benefits offered are described: AMD benefits at a glance.
Equal Opportunity Statement 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.
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