AI Technical Application Engineering Lead, AI Opensource

Position Overview

AMD is seeking a highly technical and hands-on AI Technical Application Engineering Lead to drive the development and optimization of AI applications and frameworks for AMD's datacenter GPU products and the ROCm software ecosystem. In this role, you will create cutting-edge application examples, contribute to opensource AI/ML projects, and ensure seamless integration with AMD ROCm software. You will work closely with framework maintainers and the broader AI community to implement new features, solve complex technical challenges, and mentor a team of engineers—all while pushing the limits of innovation.

Key Responsibilities

• Lead technical development of AI application examples and reference implementations showcasing AMD GPU performance across diverse AI/ML workloads.
• Architect and implement ROCm integrations for key opensource projects including vLLM, SGLang, Unsloth, and emerging AI frameworks.
• Support CI/CD and ongoing maintenance of ROCm integrations.
• Engage with developer communities and provide the necessary technical support.
• Contribute high-quality code and new features to upstream opensource projects, maintaining AMD's technical presence.
• Develop and maintain comprehensive benchmarking suites and performance analysis tools for AI workloads on AMD hardware.
• Collaborate with ROCm engineering teams to resolve performance bottlenecks, API gaps, and integration challenges.
• Design and implement end-to-end AI application pipelines demonstrating best practices for AMD GPU utilization in production environments.
• Lead cross-functional engineering efforts to optimize AI/ML frameworks on AMD datacenter GPUs.
• Mentor and guide a team of application engineers in advanced GPU programming, AI framework optimization, and opensource contribution practices.
• Drive technical roadmap alignment between AMD hardware capabilities, ROCm software features, and emerging AI application requirements.
• Analyze performance metrics, identify optimization opportunities, and implement solutions that deliver measurable improvements in AI workload throughput and efficiency.

Required Qualifications

• Hands-on experience in AI/ML application development, GPU computing, and performance optimization with significant contributions to opensource AI projects.
• Proven track record of leading technical teams and delivering complex software projects in AI/ML domains, particularly involving GPU acceleration.
• Expert-level proficiency in AI/ML frameworks such as PyTorch, TensorFlow, and JAX, with a deep understanding of their internals and optimization techniques.
• Strong programming skills in Python, C++, and CUDA/ROCm, with experience in low-level GPU programming and kernel optimization.
• Deep technical knowledge of transformer architectures, large language models, and modern AI training/inference optimization techniques.
• A master’s degree in artificial intelligence, machine learning, or a related field.
• Excellent communication skills with the ability to simplify complex technical concepts.

Preferred Qualifications

• Experience with AMD GPUs and software tools for AI/ML development.
• Familiarity with cloud platforms and containerized environments in AI/ML workflows.
• Demonstrated contributions to opensource AI projects and active community engagement.
• Experience with distributed computing, model parallelism, and scaling AI workloads across multi-GPU systems.

Benefits & Perks

• AMD Benefits at a Glance