Sr Solutions Architect, Annapurna ML

Annapurna Labs was a startup company acquired by Amazon in 2015, and is now fully integrated. If Amazon is an infrastructure company, then think Annapurna Labs as the infrastructure provider of Amazon. Our org covers multiple disciplines including silicon engineering, hardware design and verification, software, and operations. Amazon Nitro, ENA, EFA, Graviton and F1 EC2 Instances, Amazon Neuron, Inferentia and Trainium ML Accelerators, and in storage with scalable NVMe, are some of the products we have delivered, over the last few years.

The Product: Amazon Machine Learning accelerators are at the forefront of Amazon innovation. The Inferentia chip delivers best-in-class ML inference performance at the lowest cost in cloud. Trainium will deliver the best-in-class ML training performance with the most teraflops (TFLOPS) of compute power for ML in the cloud. This is all enabled by the Amazon Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and JAX. Amazon Neuron and Inferentia are used at scale with customers like Anthropic, Apple, various internal Amazon teams and more customers in various other segments.

The Team: The Amazon Annapurna Labs team is a responsible for building innovation in silicon and software for Amazon customers. We are at the forefront of innovation by combining cloud scale with the world's most talented engineers. Our team covers multiple disciplines including silicon engineering, hardware design and verification, software and operations. Because of our teams breadth of talent, we have been able to improve Amazon cloud infrastructure in networking and security with products such as Amazon Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with Amazon Graviton and the EC2 F1 FPGA instances, in storage with scalable NVMe, and now in AI and Machine Learning with Amazon Neuron SDK, Inferentia and Trainium ML accelerators.

You: In this customer-facing role, you will work closely with our Neuron software development team and strategic customers on accelerated Machine Learning solutions. You will bring your hands-on experience developing and deploying Deep Learning models and integrate it with our ML accelerator products, into large-scalable production applications.

You will need to be technically capable and credible in your own right, to become a trusted advisor for customers developing, deploying and scaling Deep Learning applications on Amazon ML accelerators. You'll succeed in this position if you enjoy capturing and sharing best practices and insights, and help shape how Amazon ML accelerator technology gets used. You will be a hands-on partner to Amazon services teams, technical field communities, sales, marketing, business development, and professional services, to drive adoption. You'll leverage your communications skills, and be very technical when doing so, to help amplify the thought-leadership around Amazon Neuron technology stack to the broader Amazon field community, as well as our customers.

Key job responsibilities

• Design architectures and own Proof of Concept (PoC) solutions for strategic customers, leveraging Amazon ML accelerators technologies and the broader set of Amazon features and services.
• Drive adoption by taking ownership of technical engagements with eco-system partners and strategic customers, assisting with the definition and implementation of technical roadmaps and enabling them to successfully deploy on Amazon ML Accelerator.
• Develop strong partnership with engineering organizations, serving as the customer advocate, to help drive product roadmap working backwards from customers feedback.
• Drive thought leadership by crafting and delivering compelling audience-specific messaging artifacts (product videos, demos, workshops, how to guides etc.) presenting Amazon ML accelerator technology through Amazon Blogs, reference architectures and solutions, and public-speaking events.
• Capture, implement and share best-practices knowledge among the Amazon technical community regarding Amazon ML Accelerators.