Software Development Engineer III, Annapurna Labs; AWS

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 is an organization within AWS UC responsible for building innovation in silicon and software for our AWS customers. We combine cloud scale with the world’s most talented engineers across disciplines including silicon engineering, hardware design, software and operations. Our work has improved 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 continue to innovate, serving startups to Global 500 companies.

AWS Neuron is the software stack for Trainium and Inferentia, the AWS Machine Learning chips. Inferentia delivers best‑in‑class ML inference performance at the lowest cost, while Trainium delivers superior training performance. Neuron includes a ML compiler and native integration into popular ML frameworks. Our products are used at scale with external customers such as Anthropic and Databricks and internal teams such as Alexa, Bedrock, Robotics, Ads and Rekognition.

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. As a technical lead you will drive the team’s vision and strategy in this critical space.

• Research implementations that deliver the best possible experiences for customers.
• Improve the time and effort it takes to port and optimise machine learning workloads on Neuron.
• Solve challenging technical problems 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.
• Mentor others and assist in the career development of team members.
• Exert technical influence to increase team productivity and effectiveness.

• 5+ years of leading design or architecture of new and existing systems.
• 5+ years of full software development life cycle experience.
• Experience as a mentor, tech lead or leading an engineering team.
• 5+ years of non‑internship professional software development experience.
• 5+ years of programming with at least one software programming language.
• Hands‑on technical experience in the Generative AI space.
• Excellent written and verbal communication skills with the ability to present complex technical information concisely to executives and non‑technical leaders.
• Experience in ML compilers, production coding agents, GenAI model architecture, model training, neural network optimisation, or applied mathematics.

• Master’s degree in computer science or equivalent.
• 2+ years in machine learning or other computational modelling environments with emphasis on hosting, building or optimising models for diverse hardware platforms.
• Proven track record in building AI agents that automate ML workload optimisation, ML compiler tuning, distributed inference and training, or ML kernel authoring and optimisation.
• Experience working with open‑source software communities in the optimisation space.
• Domain‑level knowledge of AWS services.
• Knowledge of state‑of‑the‑art…