Amazon Solutions Architect ML Infrastructure Efficient Compute 

United States, Texas, Dallas 

190073962

AWS custom ML chips provide hardware acceleration with the AWS Neuron SDK to achieve high-performance, cost-effective training and inference. Integrated with TensorFlow and PyTorch frameworks, AWS Trainium and Inferentia provide high performance and the most cost efficient DL training and inference in the cloud. Further, our P-family instances are best fit to support the production training and inference requirements with the highest performing GPUs, the most memory, and the fastest networking.Key job responsibilities
* Engage directly with customers and partners to provide them with technical advocacy on choice of accelerated infrastructure as they build on AWS. Ensure that they are spending as little time and money as possible doing so.
* Create plans, in conjunction with other members of customer and partner account teams, to define how you will help your customers with their cloud needs
* Continuously build personal expertise across a wide range of AWS services and reference architectures while providing thought leadership to customers and partners
* Share your technical knowledge broadly by participating in one-to-few and one-to-many sessions with larger groups of customers and partners.
* Work with other teams at AWS (e.g. marketing, training, APN) to contribute to the creation of content that can be delivered to the broader community at scale (e.g. online videos, and other digital content)

- 5+ years of design, implementation, or consulting in applications and infrastructures experience
- 5+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- Bachelor's degree
- Travel to client locations as needed. Estimated 30% travel requirement.

Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.