Software Development Engineer, HPC/ML Interconnect Engineer, Annapurna Labs, Annapurna Labs

1 day ago

Cupertino, United States Amazon Full time

We are seeking an experienced software engineer with low-level latency networking or interconnect expertise to optimize customer experience by designing systems that enable scaling network-intensive workloads over thousands of CPUs, GPUs, and TPUs. This role is on the forefront of AI/ML, we spend a good deal of the day optimizing the networking for the latest AI workload such as LLMs. AWS Utility Computing (UC) provides product innovations — from foundational services such as Amazon’s Simple Storage Service (S3) and Amazon Elastic Compute Cloud (EC2), to consistently released new product innovations that continue to set AWS’s services and features apart in the industry. As a member of the UC organization, you’ll support the development and management of Compute, Database, Storage, Internet of Things (IoT), Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions. Annapurna Labs (our organization within AWS UC) designs silicon and software that accelerates innovation. Customers choose us to create cloud solutions that solve challenges that were unimaginable a short time ago—even yesterday. Our custom chips, accelerators, and software stacks enable us to take on technical challenges that have never been seen before, and deliver results that help our customers change the world. Our ideal candidate will have extensive experience in low-latency networking and collective operations, such as HPC network fabric or machine learning accelerator cluster systems. Applicable experience includes high-frequency trading networking, high-speed wireless networking, or low latency interconnects such as PCIe or CXL. Proficiency in C/C++ and a deep understanding of Linux and kernel-level programming are essential. Strong problem-solving skills and the ability to troubleshoot complex networking issues are required, along with excellent communication skills to work effectively in a collaborative team environment. If you like solving hard infrastructure problems and want to work with HPC and ML customers, iterate fast, and deliver meaningful solutions at scale, then come join us A day in the life Annapurna Labs, a crucial part of AWS, is responsible for developing hardware and software components for EC2 infrastructure. Our team focuses on building networking solutions for Machine Learning (ML) and High-Performance Computing (HPC) workloads on AWS. Working at Annapurna Labs means engaging with a diverse and inclusive team culture that embraces differences and fosters a sense of belonging. You will participate in innovative learning experiences and benefit offerings, such as the CORE and AmazeCon conferences. Your day will involve designing and optimizing networking solutions, collaborating with cross-functional teams, and engaging with customers to gather feedback and continuously improve our offerings. Our team places a high value on work-life balance, believing in establishing a flow that energizes both personal and professional life. We offer flexible working hours and encourage you to find a balance that suits you, ensuring long-term happiness and fulfillment. It’s not about the number of hours spent at work or home but about creating a harmonious balance that enhances both aspects of your life. We are dedicated to supporting new team members with a mix of experience levels and tenures, fostering an environment of knowledge sharing and mentorship. Our commitment to your career growth includes assigning projects that help you develop into a well-rounded professional capable of taking on more complex tasks in the future. Join us at Annapurna Labs and be part of a team that is shaping the future of networking solutions for ML and HPC workloads on AWS The Elastic Collectives team builds out the collective operations layer in the Trainium and Nvidia stack for distributed machine learning. In any day, we are designing new algorithms, hunting for performance bottlenecks, and optimizing customers' heavy ML/AI workloads. You will be working with principal and senior principal engineers on a daily basis. This team is critical in AI at Amazon. Every customer that uses AWS for large models training and inference will be using your software, and the performance matters. If you want to make an impact in the AI industry - this is a good team for it. 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. Diverse Experiences AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying. BASIC QUALIFICATIONS - 3+ years of non-internship professional software development experience - 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience - Experience programming with at least one software programming language PREFERRED QUALIFICATIONS - 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience - Bachelor's degree in computer science or equivalent 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. #J-18808-Ljbffr

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