Deep expertise in gpu and trainium hardware architecture
Proficiency in distributed training strategies for large models
Experience with inference optimization frameworks like vllm and triton
This role focuses on defining and deploying strategies to accelerate the adoption of AWS compute and ML services for frontier AI model builders
Job Summary
This role focuses on defining and deploying strategies to accelerate the adoption of AWS compute and ML services for frontier AI model builders.
The specialist will provide deep technical guidance on optimizing both model training and inference serving at scale using advanced hardware and software stacks.
Candidates must possess a unique blend of infrastructure systems background and hands-on machine learning expertise to lead engagements with startup customers.
Matching Summary
This role focuses on defining and deploying strategies to accelerate the adoption of AWS compute and ML services for frontier AI model builders.
Salary
Not specified; Not specified; Not specified
Skills & Requirements
Must-have
Deep expertise in GPU and Trainium hardware architecture
Proficiency in distributed training strategies for large models
Experience with inference optimization frameworks like vLLM and Triton
Knowledge of AWS SageMaker HyperPod and EKS orchestration
Ability to design scalable AI infrastructure for startups
Nice-to-have
Strong communication skills for C-Level executives
Experience collaborating with open-source ML communities
Background in model fine-tuning techniques like LoRA and RLHF
Proven track record in building technical content and demos
Familiarity with NVIDIA Nsight and DCGM profiling tools
Key Requirements
Deep infrastructure and systems background combined with ML/AI expertise
Expert-level knowledge of GPU architectures and networking protocols
Ability to articulate technical benefits to platform engineers and executives