FAE/ Field Support Manager at Advanced Micro Devices, Inc

, , Taiwan -

Full Time

Start Date

Immediate

Expiry Date

30 Jan, 26

Salary

0.0

Posted On

01 Nov, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

GPU Server Software, AI/ML, HPC, Python, C/C++, CUDA, AI Frameworks, LLM Training, Distributed Training, Linux OS, Docker, Kubernetes, Performance Profiling, Debugging Tools, Communication Skills, Presentation Skills

Industry

Semiconductor Manufacturing

Description

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. Job Summary We are seeking a highly skilled Field Application Engineer (FAE) specializing in GPU server software and AI/LLM model enablement. This role focuses on providing technical expertise for GPU-based server platforms, including software integration, performance optimization, and customer enablement for AI, HPC, and cloud workloads. You will act as the technical liaison between engineering teams and customers to ensure successful deployment of GPU server solutions for training and inference of large-scale models. Key Responsibilities Customer Engagement & Technical Support Serve as the primary technical contact for customers on GPU server software and AI workloads. Assist customers with installation, configuration, and optimization of GPU drivers, CUDA libraries, and AI frameworks. Pre-Sales & Post-Sales Activities Deliver technical presentations and demos showcasing GPU server capabilities for AI/LLM workloads. Support proof-of-concept (POC) projects and guide customers through deployment. Software Integration & Troubleshooting Diagnose and resolve software-related issues, including driver compatibility, performance bottlenecks, and API integration. Collaborate with internal engineering teams to escalate and resolve complex technical challenges. Coding & Development for AI/LLM Develop sample codes, scripts, and automation tools for GPU-based AI training and inference. Write and optimize code in Python, C/C++, CUDA, and integrate with AI frameworks (e.g., PyTorch, TensorFlow). Implement and fine-tune LLM training pipelines, inference optimization, and distributed GPU workloads. Work with SGlang or similar frameworks for structured generation and inference acceleration. Performance Tuning & Benchmarking Conduct performance analysis and tuning for GPU workloads (AI/ML, LLM, HPC). Provide best practices for optimizing GPU utilization and scaling across multi-GPU clusters. Training & Documentation Develop and deliver technical training for customers and partners on AI/LLM deployment. Create technical documentation, application notes, and troubleshooting guides. Qualifications Bachelor’s or Master’s degree in Computer Engineering, Electrical Engineering, or related field. Good experience in GPU server software, AI/ML, or HPC environments. Strong coding skills in Python, C/C++, CUDA; experience with AI/ML frameworks (PyTorch, TensorFlow). Familiarity with LLM training/inference, distributed training, and optimization techniques. Experience with Linux OS, container technologies (Docker, Kubernetes), and cloud platforms. Hands-on experience with performance profiling and debugging tools. Excellent communication and presentation skills for customer-facing roles. Preferred Skills Experience with SGlang, Hugging Face Transformers, or similar LLM toolkits. Knowledge of GPU virtualization, multi-GPU scaling, and mixed-precision training. Familiarity with CI/CD pipelines and Git for collaborative development. Ability to work independently and manage multiple customer engagements. #LI-SC1 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.

Responsibilities

The Field Application Engineer will serve as the primary technical contact for customers, assisting with GPU server software and AI workloads. Responsibilities include software integration, performance optimization, and customer enablement for AI, HPC, and cloud workloads.