AI Cluster Validations For Distributed Training and Inference 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. THE ROLE: AMD is looking for an AI solutions validation Engineer who is passionate about complex AI solutions, AI infrastructure, building cluster scale automation for distributed training and inference workloads, MLOps. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology.  THE PERSON: The ideal candidate should be passionate about software engineering, system design, validation, automation and possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD. KEY RESPONSIBILITIES: Work with AMD’s architecture specialists to validate AI solutions for distributed training and inference workloads with AMD's ROCM software Build cluster scale automation for distributed training and inference workloads Publish reference designs and benchmark numbers for AI workloads Apply a data minded approach to target optimization efforts Design and develop new groundbreaking AMD technologies Participating in new ASIC and hardware bring ups Develop technical relationships with peers and partners PREFERRED EXPERIENCE: Good experience with complex compute systems used in AI, HPC deployments, backend network designs in RDMA clusters Experience in validating complex AI infrastructure - GPUs, networking, ROCEv2, UEC, running benchmark tests like IBPerf benchmarking, RCCL/NCCL. Experience with running training of LLMs, MoE models, Image Generation, recommendations models with different frameworks like PyTorch, Tensorflow, Megatron-LM, JAX. Running training performance benchmarks. Experience with running inference workloads in AI clusters with different inference frameworks like vLLM, SGLang. Running performance benchmarks for inference. Experience with distributed systems and schedulers like Kubernetes, Slurm Ability to write high quality automation frameworks and scripts using Python or Golang Experience with performance profiling of CPUs, GPUs and debugging complex compute, network, storage problems. Experience with AMD ROCM would be an added advantage Experience with Linux, Windows operating systems Effective communication and problem-solving skills PREFERRED ACADEMIC CREDENTIALS: Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent #LI-G11 #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.

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.

THE ROLE: AMD is looking for an AI solutions validation Engineer who is passionate about complex AI solutions, AI infrastructure, building cluster scale automation for distributed training and inference workloads, MLOps. You will be a member of a core team of incredibly talented industry specialists and will work with the very latest hardware and software technology.  THE PERSON: The ideal candidate should be passionate about software engineering, system design, validation, automation and possess leadership skills to drive sophisticated issues to resolution. Able to communicate effectively and work optimally with different teams across AMD. KEY RESPONSIBILITIES: Work with AMD’s architecture specialists to validate AI solutions for distributed training and inference workloads with AMD's ROCM software Build cluster scale automation for distributed training and inference workloads Publish reference designs and benchmark numbers for AI workloads Apply a data minded approach to target optimization efforts Design and develop new groundbreaking AMD technologies Participating in new ASIC and hardware bring ups Develop technical relationships with peers and partners PREFERRED EXPERIENCE: Good experience with complex compute systems used in AI, HPC deployments, backend network designs in RDMA clusters Experience in validating complex AI infrastructure - GPUs, networking, ROCEv2, UEC, running benchmark tests like IBPerf benchmarking, RCCL/NCCL. Experience with running training of LLMs, MoE models, Image Generation, recommendations models with different frameworks like PyTorch, Tensorflow, Megatron-LM, JAX. Running training performance benchmarks. Experience with running inference workloads in AI clusters with different inference frameworks like vLLM, SGLang. Running performance benchmarks for inference. Experience with distributed systems and schedulers like Kubernetes, Slurm Ability to write high quality automation frameworks and scripts using Python or Golang Experience with performance profiling of CPUs, GPUs and debugging complex compute, network, storage problems. Experience with AMD ROCM would be an added advantage Experience with Linux, Windows operating systems Effective communication and problem-solving skills PREFERRED ACADEMIC CREDENTIALS: Bachelor’s or Master's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent #LI-G11 #LI-HYBRID