Description

　　At AWS AI, we want to make it easy for our customers to train their deep learning workload in the cloud. With Amazon SageMaker, AWS is building customer-facing services to empower data scientists and software engineers in their deep learning endeavors. As our customers rapidly adopt LLMs and Generative AI for their business, we’re building the next-generation AI platform to accelerate their development. We’re seeking a dedicated engineering team lead to drive building our next-generation AI compute platform that’s optimized for LLMs and distributed training.

　　As an SDE, you will be responsible for designing, developing, testing, and deploying distributed machine learning systems and large-scale solutions for our world-wide customer base. In this, you will collaborate closely with a team of ML scientists and customers to influence our overall strategy and define the team’s roadmap. You'll assist in gathering and analyzing business and functional requirements, and translate requirements into technical specifications for robust, scalable, supportable solutions that work well within the overall system architecture. You will also drive the system architecture, spearhead best practices that enable a quality product, and help coach and develop junior engineers. A successful candidate will have an established background in engineering large scale software systems, a strong technical ability, great communication skills, and a motivation to achieve results in a fast paced environment.

　　About You:

　　You are passionate about building platform and products for large scale deep learning model training (100+ billion parameter GPT, 1000s of GPU devices). You have a proven track record of bringing innovative research to customers. You are able to thrive and succeed in an entrepreneurial environment and not be hindered by ambiguity or competing priorities. Ownership, delivering results, thinking big and analytical leadership are essential to success in this role.

　　You have solid experience in multi-threaded asynchronous C++/Go development. You have prior experience in one of: resource orchestrators like slurm/kubernetes, high performance computing, building scalable systems, experience in large language model training.

　　This is a great team to come to have a huge impact on AWS and the world's customers we serve!

　　A day in the life

　　Every day will bring new and exciting challenges on the job while you:

　　Build and improve next-generation AI platform

　　Collaborate with internal engineering teams, leading technology companies around the world and open source community - PyTorch, NVIDIA/GPU

　　Create innovative products to run at scale on the AI platform, and see them launched in high volume production

　　About the team

　　Inclusive Team Culture

　　Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 14 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

　　Work/Life Balance

　　Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

　　Mentorship & Career Growth

　　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.

　　We are open to hiring candidates to work out of one of the following locations:

　　Bellevue, WA, USA | Santa Clara, CA, USA | Seattle, WA, USA

　　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

　　Master's degree in computer science or equivalent

　　Experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems

　　Experience in machine learning, data mining, information retrieval, statistics or natural language processing

　　Experience with deep learning frameworks and libraries (any of PyTorch, TensorFlow, Huggingface, etc.)

　　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 $115,000/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. Applicants should apply via our internal or external career site.