Description

AWS Neuron is the complete software stack for the AWS Inferentia and Trainium cloud-scale machine

learning accelerators and servers that use them. This role is for a software engineer in the Machine Learning Inference Model Enablement and Generality team for AWS Neuron at Annapurna Labs.

This role is responsible for development, enablement and performance tuning of a wide variety of LLM model families, including massive scale large language models like the Llama family, DeepSeek and beyond, as well as stable diffusion, vision transformers and many more.

The Inference Model Enablement and Generality team works side by side with compiler engineers and runtime engineers to create, build and tune distributed inference solutions with Trainium and Inferentia. Experience optimizing LLM inference performance for both latency and throughput is highly desired. Experience with distributed inference libraries such as vLLM is a bonus.

Key job responsibilities

This role will help lead the efforts building distributed inference support for Pytorch in the Neuron SDK. This role will tune these models to ensure highest performance and maximize the efficiency of them running on the customer AWS Trainium and Inferentia silicon and servers. Strong software development using Python and ML knowledge are both critical to this role.

A day in the life

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.

Work in a startup-like development environment, where you're always working on the most important stuff.

About the team

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we're building an environment that celebrates knowledge-sharing and mentorship. Our senior members enjoy one-on-one mentoring and thorough, but kind, code reviews. We care about your career growth and strive to assign projects that help our team members develop your engineering expertise so you feel empowered to take on more complex tasks in the future.

Basic Qualifications

5+ years of non-internship professional software development experience

5+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience

Fundamentals of Machine learning and LLMs, their architecture, training and inference lifecycles along with work experience on some optimizations for improving the model execution.

Experience programming with at least one software programming language

Preferred Qualifications

5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience

Masters degree in computer science or equivalent

Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $151,300/year in our lowest geographic market up to $261,500/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits . This position will remain posted until filled. Applicants should apply via our internal or external career site.