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Machine Learning Engineer II, Annapurna ML

Job ID: 2677595 | Annapurna Labs (U.S.) Inc.

DESCRIPTION

Annapurna ML pathfinding team is a new function within the Annapurna ML go-to-market org that help customers accelerate their adoption of Annapurna ML products including AWS Trainium and AWS Inferentia. The team offers hands-on data science and coding services to our most strategic customer opportunities to launch their training and inference workloads on AWS purpose built ML silicon offerings.



Key job responsibilities
In this customer-facing role, you will be responsible for helping our most strategic customers port their models to the AWS Trainium & Inferentia platforms by delivering high-quality code and customizations to make the models functional and performant. You will use and provide feedback to the various Neuron SDK libraries and help prototype and develop new features based on the latest research findings and customer requests.

A day in the life
You will be required to assist our most strategic customers in porting their models to AWS Trainium and Inferentia.

You will work directly with customer data scientists and ML engineering teams and write code to have the models be performant on AWS purpose-built silicon solutions. It may require low-level coding in C++ and writing custom kernels to get the best performance possible.

You will also be responsible for porting the latest open-source models to AWS Trainium/Inferentia. You will also contribute to open-source projects to help add support for AWS Trainium/Inferentia in popular projects.

It will require a close collaboration with the Neuron engineering team to help drive the Neuron product roadmap and give feedback on improving product quality.

About the team
Our team's mission is to provide the fastest, cost-effective and user-friendly place to train and deploy Generative AI workloads in the cloud. The team provides white-glove service to our most strategic customers to implement their models for both training and inference using the Neuron SDK associated libraries and APIs.

BASIC QUALIFICATIONS

- 3+ years of non-internship professional software development experience
- 3+ years of programming using a modern programming language such as Java, C++, or C#, including object-oriented design experience
- 3+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- 2+ years of experience writing code to train and/or deploy deep learning models in PyTorch

PREFERRED QUALIFICATIONS

- Bachelor's degree in computer science or equivalent
- Experience deploying Generative AI applications with large language or vision models into production.

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.

Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $129,300/year in our lowest geographic market up to $223,600/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.