Sr. Solutions Architect
- Flexible / Remote
The Product: AWS Machine Learning accelerators are at the forefront of AWS 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 cutting edge software stack, the AWS Neuron Software Development Kit (SDK), which includes an ML compiler, runtime and natively integrates into popular ML frameworks, such as PyTorch, TensorFlow and MxNet. AWS Neuron and Inferentia are used at scale with customers like Snap, Autodesk, Amazon Alexa, Amazon Rekognition 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 AWS 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 AWS cloud infrastructure in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), in compute with AWS Graviton and the EC2 F1 FPGA instances, in storage with scalable NVMe, and now in AI and Machine Learning with AWS 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 cutting edge 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 AWS ML accelerators. You'll succeed in this position if you enjoy capturing and sharing best practices and insights, and help shape how AWS ML accelerator technology gets used. You will be a hands-on partner to AWS 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 AWS Neuron technology stack to the broader AWS field community, as well as our customers.
Roles & Responsibilities:
• Design architectures and own Proof of Concept (PoC) solutions for strategic customers, leveraging AWS ML accelerators technologies and the broader set of AWS 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 AWS 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 AWS ML accelerator technology through AWS Blogs, reference architectures and solutions, and public-speaking events.
• Capture, implement and share best-practices knowledge among the AWS technical community regarding AWS ML Accelerators.
• 7 or more years of progressive technical experience as a Data Scientist, Machine Learning engineer, Solutions Architect, Software or System Engineer, with at least 3 years as a Solution Architect, Consultant or similar customer facing technical roles.
• 3 or more years' experience working with large enterprises, with demonstrated ability to think strategically about technical, product, and business challenges.
• 3+ years of experience accelerating ML training and inference models such as PyTorch, TensorFlow, and MxNet in production environments
• 3+ years of experience in OS, network, and system software design
• 3+ years of experience consulting senior management and engineering teams with technical advice
• Strong written communications skills, with high level of comfort communicating effectively across internal and external organizations, with both technical and non-technical audiences.
• Deep domain knowledge in applications of Deep Learning and other ML techniques in production environments.
• Proficiency in at least one major ML frameworks: TensorFlow, PyTorch, or MXnet
• Experience using hardware accelerators for Deep Learning workloads, model optimization and compilation, using industry DL compilers (TensorFlow XLA, TensorRT, TVM).
• An advanced degree in computer science, engineering or mathematics.
• AWS certification (e.g. AWS Solutions Architect Associate or Professional, AWS ML Specialty)
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.
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