Cloud AI Systems Engineer for Generative ML Infra

Amazon Web Services (AWS); Cupertino (CA); On-site; USD 149,000 - 201,000; Full time

Job summary

Annapurna Labs (U.S.) Inc. in Cupertino, CA, is seeking a seasoned hardware/software engineer to join the AWS Hardware Engineering team. You will tackle complex architectural problems, own system-level design, and drive reliability and testability for accelerators and cloud servers.

You will collaborate with SDEs, hardware engineers, and TPMs, decompose big problems, automate workflows, and contribute to AI-driven tooling that scales AWS cloud infrastructure.

Qualifications

• 2+ years of non-internship professional software development experience.
• 1+ years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience.
• 7+ years of administrative experience in networking, storage systems, operating systems and hands-on systems engineering experience.
• Knowledge of systems engineering fundamentals (networking, storage, operating systems).
• Experience programming with at least one modern language such as C++, C#, Java, Python, Golang, PowerShell, Ruby.

Responsibilities

• You will be a technical leader solving complex architectural problems which may not defined before hand.
• You will decompose big difficult server system testability, reliability and diagnosis problems into straightforward tasks, components or features that you will lead to deliver yourself and through others in parallel.
• A day in the life working with various roles and groups to ensure high quality designs and reliable deployments for AWS Accelerated server solutions.

Skills

C++

C#

Java

Python

Golang

PowerShell

Ruby

Job description

Annapurna Labs (U.S.) Inc. in Cupertino, CA, is seeking a seasoned hardware/software engineer to join the AWS Hardware Engineering team. You will tackle complex architectural problems, own system-level design, and drive reliability and testability for accelerators and cloud servers.

You will collaborate with SDEs, hardware engineers, and TPMs, decompose big problems, automate workflows, and contribute to AI-driven tooling that scales AWS cloud infrastructure.