Staff Applied Machine Learning Software Engineer - Generative AI

AMD - San Jose, CA

Full-time - Mid Level

San Jose, CA

Computer and Electronic Product Manufacturing

About the position

The Staff Applied Machine Learning Software Engineer - Generative AI at AMD is responsible for developing and optimizing software solutions for Generative AI applications. This role involves working on state-of-the-art research and implementing innovative software development techniques to enhance AMD's AI inference capabilities across various products. The engineer will collaborate with multiple teams to shape the future of AI solutions, focusing on model optimization, performance analysis, and custom kernel development.

Responsibilities

• Accelerate inference of Generative AI on AMD's products.
• Develop tools and techniques for model analysis, profiling, performance projections and analyzing architecture bottlenecks.
• Architect and prototype custom kernels on GPUs and CPUs (HIP, CUDA, OpenCL, Triton, etc.).
• Optimize deep learning inference pipeline including graph compilation using AMD AI compilers.
• Reproduce and improve upon state-of-the-art quantization, pruning, optimization algorithms in Pytorch and Python.
• Develop high quality software to enable next-gen solutions.
• Collaborate with AI/ML frameworks and infrastructure teams to enable new algorithms in the platforms.
• Collaborate with AMD Research and Architecture teams to improve future products.
• Influence the direction of AI/ML platforms for inference and training.

Requirements

• Deep understanding of foundational AI model architectures.
• Proficiency in software development and AI/ML frameworks such as Pytorch.
• Experience with quantization and sparsity algorithms.
• Demonstrated ability to efficiently map AI models onto GPUs and/or other hardware accelerators.
• Strong development and debugging skills in Python.
• Experience in C++ programming for GPUs and/or custom accelerators.

Nice-to-haves

• Solid understanding of CNN, Transformer model architectures, LLMs, Stable Diffusion models.
• Experience with model optimization, including quantization, sparsity algorithms.
• Familiarity with torch.fx and/or other AI compilers, execution runtime.
• Highly preferred - knowledge of custom accelerator hardware.
• Knowledge of LLMs/LMMs finetuning methods like RLHF.
• Knowledge of parameter efficient techniques like LoRA QLoRA.
• Contributions to open ML research or developer community.

Benefits

• Base pay dependent on skills and experience.
• Eligibility for annual bonus or sales incentive.
• Opportunity to own shares of AMD stock.
• Discount on AMD stock through Employee Stock Purchase Plan.
• Competitive benefits package.