60 Amd Manufacturing Engineer Jobs Hiring Near You

Job Summary:
AMD is a company focused on building products that accelerate next-generation computing experiences. The role involves driving the performance of post-training workloads on AMD Instinct™ GPUs, optimizing training performance, and collaborating with various teams to improve engineering productivity and reproducibility.
Responsibilities:
• Lead performance for fine-tuning and RL training solutions on AMD GPUs.
• Improve throughput, memory efficiency, and stability across data, model, optimizer, and runtime steps.
• Optimize multi-GPU and multi-node training performance, including communication and scaling behavior.
• Contribute efficient kernels/ops and targeted graph-level or runtime-level optimizations where they deliver the highest impact.
• Profile, diagnose, and resolve bottlenecks using standard tooling; prevent regressions in CI and benchmarking pipelines.
• Build and apply agentic or AI-assisted workflows to accelerate profiling analysis, experiment generation, regression triage, and performance debugging.
• Develop scalable tooling and automation to improve reproducibility, performance reporting, and optimization velocity across teams.
• Ship reproducible pipelines and documentation adopted by internal teams and external developers.
• Collaborate with framework, compiler, kernel, and model teams to land durable performance improvements.
Qualifications:
Required:
• Drive the performance of post-training workloads on AMD Instinct™ GPUs.
• Work across kernels, distributed training, compiler and framework integrations, and AI-assisted engineering workflows to deliver fast, stable, and reproducible fine-tuning and RL training pipelines on ROCm.
• Hands-on performance engineering.
• Apply agentic and AI-assisted workflows to accelerate profiling, root-cause analysis, experiment orchestration, regression triage, and optimization at scale.
• Lead performance for fine-tuning and RL training solutions on AMD GPUs.
• Improve throughput, memory efficiency, and stability across data, model, optimizer, and runtime steps.
• Optimize multi-GPU and multi-node training performance, including communication and scaling behavior.
• Contribute efficient kernels/ops and targeted graph-level or runtime-level optimizations where they deliver the highest impact.
• Profile, diagnose, and resolve bottlenecks using standard tooling; prevent regressions in CI and benchmarking pipelines.
• Build and apply agentic or AI-assisted workflows to accelerate profiling analysis, experiment generation, regression triage, and performance debugging.
• Develop scalable tooling and automation to improve reproducibility, performance reporting, and optimization velocity across teams.
• Ship reproducible pipelines and documentation adopted by internal teams and external developers.
• Collaborate with framework, compiler, kernel, and model teams to land durable performance improvements.
• B.S., M.S., or Ph.D. in Computer Science, Computer Engineering, Electrical Engineering, or equivalent.
Preferred:
• Proven GPU performance engineering for deep learning workloads (ROCm/HIP, Triton, or similar).
• Hands-on experience with SFT, LoRA, and RL-based training at scale.
• Strong PyTorch experience, including torch.distributed, FSDP/ZeRO, or equivalent distributed training approaches.
• Proficient in Python and C++; comfortable reading and writing kernels when needed.
• Experience with distributed systems and collective communication libraries.
• Track record of turning profiles into fixes, upstreaming changes, and documenting measurable results.
• Experience building or using AI-assisted developer workflows, agentic tooling, or automation for performance analysis, experiment management, or engineering productivity is a plus.
• Ability to balance deep technical investigation with practical automation and cross-functional execution.
Company:
Advanced Micro Devices is a semiconductor company that designs and develops graphics units, processors, and media solutions. Founded in 1969, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.