Staff Applied Machine Learning Software Engineer – Generative AI

WHAT YOU DO AT AMD CHANGES EVERYTHING We care deeply about transforming lives with AMD technology to enrich our industry, our communities, and the world.

Our mission is to build great products that accelerate next-generation computing experiences the building blocks for the data center, artificial intelligence, PCs, gaming and embedded.

Underpinning our mission is the AMD culture. We push the limits of innovation to solve the world’s most important challenges.

We strive for execution excellence while being direct, humble, collaborative, and inclusive of diverse perspectives. AMD together we advance Staff Applied Machine Learning Software Engineer Generative AI The Role The AI Group at AMD is searching for talented and motivated engineers and scientists to work on Generative AI inference solutions.

You will explore and improve upon state-of-the-art research in both academia and industry and innovate in the areas of software development, model optimization and compression algorithms for Generative AI applications such as LLMs, Stable Diffusion and Multi Modal Models.

You will be a part of the core AI Solutions team enabling GenAI on a wide variety of AMD’s products such as RyzenAI XDNA / NPU, CPU, GPU and embedded architectures.

Your work will shape and influence AMD’s inference and training solutions across the software stack from frameworks like Pytorch / ONNX to custom hardware like NPU / GPU.

The Person If you are passionate about software engineering, reading latest literature, producing novel ideas, leading implementation of those ideas through high quality code, push the boundaries on scale and performance, then this is a perfect role for you.

You will be someone with a deep understanding of foundational AI model architectures, software development, AI / ML frameworks such as Pytorch, quantization and sparsity algorithms.

You will have demonstrated efficiently mapping AI models on to GPUs and / or other hardware accelerators. You are someone who can work in a dynamic, fast-paced development environment with excellent collaboration skills with a spirit of innovation.

You will work with multiple engineering teams that are geographically dispersed. You will work on next generation framework software, guiding other senior developers and domain experts.

Key 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.

Team player and ready to work with a geographically distributed team. Influence the direction of AI / ML platforms for inference and training.

Preferred Experience Solid understanding of CNN, Transformer model architectures, LLMs, Stable Diffusion models. Strong development and debugging skills in Python.

Experience with model optimization, including quantization, sparsity algorithms. Experience in development with ML frameworks such as PyTorch, ONNXRuntime, JAX, TensorFlow.

Familiarity with torch.fx and / or other AI compilers, execution runtime. Experience in C++ programming for GPUs and / or custom accelerators 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 Strong communication and problem-solving skills.

ACADEMIC CREDENTIALS (Please Do Not Apply Unless You Have) BS, MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related technical fields.

Location : San Jose, California. #LI-JT1 At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position.

You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan.

You’ll also be eligible for competitive benefits described in more detail here. 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.

Staff Applied Machine Learning Software Engineer Generative AI The Role The AI Group at AMD is searching for talented and motivated engineers and scientists to work on Generative AI inference solutions.

You will explore and improve upon state-of-the-art research in both academia and industry and innovate in the areas of software development, model optimization and compression algorithms for Generative AI applications such as LLMs, Stable Diffusion and Multi Modal Models.

You will be a part of the core AI Solutions team enabling GenAI on a wide variety of AMD’s products such as RyzenAI XDNA / NPU, CPU, GPU and embedded architectures.

Your work will shape and influence AMD’s inference and training solutions across the software stack from frameworks like Pytorch / ONNX to custom hardware like NPU / GPU.

The Person If you are passionate about software engineering, reading latest literature, producing novel ideas, leading implementation of those ideas through high quality code, push the boundaries on scale and performance, then this is a perfect role for you.

You will be someone with a deep understanding of foundational AI model architectures, software development, AI / ML frameworks such as Pytorch, quantization and sparsity algorithms.

You will have demonstrated efficiently mapping AI models on to GPUs and / or other hardware accelerators. You are someone who can work in a dynamic, fast-paced development environment with excellent collaboration skills with a spirit of innovation.

You will work with multiple engineering teams that are geographically dispersed. You will work on next generation framework software, guiding other senior developers and domain experts.

Key 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.

Team player and ready to work with a geographically distributed team. Influence the direction of AI / ML platforms for inference and training.

Preferred Experience Solid understanding of CNN, Transformer model architectures, LLMs, Stable Diffusion models. Strong development and debugging skills in Python.

Experience with model optimization, including quantization, sparsity algorithms. Experience in development with ML frameworks such as PyTorch, ONNXRuntime, JAX, TensorFlow.

Familiarity with torch.fx and / or other AI compilers, execution runtime. Experience in C++ programming for GPUs and / or custom accelerators 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 Strong communication and problem-solving skills.

ACADEMIC CREDENTIALS (Please Do Not Apply Unless You Have) BS, MS or PhD in Computer Science, Computer Engineering, Electrical Engineering, or related technical fields.

Location : San Jose, California. #LI-JT1At AMD, your base pay is one part of your total rewards package. Your base pay will depend on where your skills, qualifications, experience, and location fit into the hiring range for the position.

You may be eligible for incentives based upon your role such as either an annual bonus or sales incentive. Many AMD employees have the opportunity to own shares of AMD stock, as well as a discount when purchasing AMD stock if voluntarily participating in AMD’s Employee Stock Purchase Plan.

You’ll also be eligible for competitive benefits described in more detail here. 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.