Software Development Engineer, ML Systems, Annapurna Labs

Description

About the Team The Neuroboros team was recently created to pursue the ambitious goal of leveraging and expanding Generative AI technologies to help customers benefit from the scale and price/performance equation offered by Amazon Machine Learning hardware. The creation of the team in NYC is key to Annapurna Labs’ location strategy, with the goal of creating an additional hub attracting top talent with varied backgrounds to work on challenging problems, using and building state-of-the-art tooling.

Amazon Annapurna Labs team (our organization within AWS UC) is responsible for building innovation in silicon and software for our 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, software and operations. Because of our team’s breadth of talent, we have been able to improve AWS cloud infrastructure in high-performance machine learning with AWS Neuron, Inferentia and Trainium ML chips, in networking and security with products such as AWS Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), and in computing with AWS Graviton and F1 EC2 instances.

Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

AWS Neuron is the software of Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best-in-class ML inference performance at the lowest cost in the cloud to our AWS customers. Trainium is designed to deliver the best-in-class ML training performance at the lowest training cost in the cloud, and it’s all being enabled by AWS Neuron. Neuron is a Software that include ML compiler and native integration into popular ML frameworks.

Our products are being used at scale with external customers like Anthropic and Databricks as well as internal customers like Alexa, Amazon Bedrock, Amazon Robotics, Amazon Ads, Amazon Rekognition and many more.

You will join a dynamic team working at the cutting edge of the GenAI revolution by applying AI to AI. You will work on building agents, tools, and models to simplify and accelerate customer adoption of Neuron, the software stack supporting Amazon's Machine Learning silicon:
Trainium. Partnering with external and internal customers, you will identify key obstacles and opportunities to accelerate their migration to AWS's ML silicon. You will be a key contributor driving impact by building AI agents and tools that simplify AWS Neuron adoption, which is critical to AWS's Generative AI business.

• Research implementations that deliver the best possible experiences for customers.
• Deliver on goals to improve the time and effort it takes to port and optimize Machine Learning workloads on Neuron.
• Solve challenging technical problems, often ones not solved before, at every layer of the stack
• Design, implement, test, deploy and maintain innovative software solutions to transform service performance, durability, cost, and security.
• Build high-quality, highly available, always-on products.
• Potentially contribute intellectual property through patents

As You Design And Code Solutions To Help Our Team Drive Efficiencies In Software Architecture, You’ll Create Metrics, Implement Automation And Other Improvements, And Resolve The Root Cause Of Software Defects. You’ll Also

• Build high-impact solutions to deliver to our large customer base.
• Participate in design discussions, code review, and communicate with internal and external stakeholders.
• Work cross-functionally to help drive business decisions with your technical input. You will collaborate closely with a cross-functional team comprised of compiler, hardware, and ML engineers.
• Work in a startup-like development environment, where you’re always working on the most important stuff.