Software Development Engineer, Generative AI, Annapurna Labs - Neuroboros Team

Description 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 Amazon Neuron adoption, which is critical to Amazon’s Generative AI business.

Key job responsibilities

Responsibilities This role requires collaborating with other Neuron Software teams, Science, AWS AI Services, external partners and customers with a potential high impact on Amazon’s top and bottom line. As a member of the team applying Generative AI to accelerate Neuron adoption, you will play a key role in shaping this space with the following technical responsibilities:

• 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.
• Build and operate agentic evaluation frameworks, monitoring, and feedback loops that ensure the correctness, reliability, and continuous improvement of AI agents
• 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

About The Team We 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.

About Amazon Annapurna Labs Amazon Annapurna Labs team (our organization within AWS UC) is responsible for building innovation in silicon and software for our 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, 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 Neuron, Inferentia and Trainium ML chips, in networking and security with products such as Nitro, Enhanced Network Adapter (ENA), and Elastic Fabric Adapter (EFA), and in computing with Graviton and F1 EC2 instances.

Basic Qualifications

• Experience in written and verbal communication with the ability to present complex technical information in a clear and concise manner to executives and non-technical leaders
• 3+ years of relevant, broad engineering experience.
• Computer Science core: object-oriented design, data structures, and performance analysis with at least 2 programming languages.
• Hands-on technical experience working in the Generative AI space
• Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations.
• Experience in one or more of the following areas: ML compilers, production coding agents, GenAI model architecture, model training, neural network optimization, or alternatively applied math.
• Passion for customer experience and usability, including successful delivery of customer self-service tools and automated management/optimization of services, and a strong services orientation

Preferred Qualifications

• Bachelor’s or Master’s degree in computer science or equivalent
• 2+ years in machine learning or other computational modeling environments with an emphasis on hosting, building or optimizing models for diverse hardware platforms
• Proven track record in building AI agents that automate ML workload optimization, ML compiler tuning, distributed inference and training, or ML kernel authoring and optimization
• Experience working with open-source software communities in the optimi…