AI/ML Solutions Engineer for Enterprise GPU Deployments

Advanced Micro Devices, Inc.; Santa Clara (CA); Híbrido; USD 150 000 - 230 000; Tempo integral

Resumo da oferta

Advanced Micro Devices, Inc. seeks an AI/ML Solutions Engineer in Santa Clara to empower customers and partners to adopt AMD’s AI software stack.

You will lead reference designs, optimize workflows, and drive end-to-end AI deployments across training, fine-tuning, and inference on AMD GPUs. The ideal candidate has deep ML/AI systems expertise, strong collaboration skills, and the ability to translate enterprise workloads into scalable engineering directions while engaging with customers, ISVs,

Qualificações

• Deep expertise in ML/AI systems and ability to work with customers and cross-functional teams.
• Experience with modern ML workloads (LLMs, GenAI, RAG) and GPU workflows.
• Strong communication and technical advocacy, translating customer needs into engineering direction.

Responsabilidades

• Work across reference design creation, workflow optimization, performance tuning and ecosystem enablement.
• Prototype and demonstrate end-to-end AI workflows across training, fine-tuning, and inference; develop validated designs and performance playbooks.

Conhecimentos

AI/ML engineering

Distributed training

GPU computing

PyTorch

TensorFlow

JAX

Inference runtimes

Containerized GPU environments

ROCm

CUDA

MLOps

Cloud-native architectures

Demos / content development

Customer engagement

Formação académica

BS, MS, or PhD in Computer Science or related

Ferramentas

PyTorch

TensorFlow

JAX

Docker

Kubernetes

Descrição da oferta de emprego

Advanced Micro Devices, Inc. seeks an AI/ML Solutions Engineer in Santa Clara to empower customers and partners to adopt AMD’s AI software stack.

You will lead reference designs, optimize workflows, and drive end-to-end AI deployments across training, fine-tuning, and inference on AMD GPUs. The ideal candidate has deep ML/AI systems expertise, strong collaboration skills, and the ability to translate enterprise workloads into scalable engineering directions while engaging with customers, ISVs,