DESCRIPTION

AWS Utility Computing (UC) provides 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, Platform, and Productivity Apps services in AWS, including support for customers who require specialized security solutions for their cloud services. Additionally, this role may involve exposure to and experience with Amazon’s growing suite of generative AI services and other cutting-edge cloud computing offerings across the AWS portfolio.

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.

In Annapurna Labs we are at the forefront of hardware/software co-design not just in Amazon Web Services (AWS) but across the industry. The Machine Learning Fleet Operations Team is looking for candidates interested in diving deep into our “fleet” of Machine Learning servers deployed around the world.

Do you like solving mysteries? Great! Figuring out what that light switch with no obvious function actually does? Me too! Are you wearing a smartwatch to monitor your sleep and activity over time to optimize your routines? You’ll fit right in. Does the word exabyte excite you? Let’s get to work.

We are seeking an engineer who is comfortable debugging emergent problems in GPU and server hardware, writing scripts in languages such as Python, Bash and/or Golang, running large scale experiments on a fleet of complex hardware, developing data infrastructure and analyzing trends, and developing automation software to scale operations.

Our team has end to end ownership of some of the most advanced server hardware in the world. We drive technical debug efforts and write truly massive scale autonomous software to monitor, optimize, and remediate machine learning hardware. Come join us!

Key job responsibilities
– Member of a team responsible for system remediation, operational excellence, and customer experience on bleeding edge ML products
– Utilize data to root cause hardware failures and identify live trends on the most complex systems in AWS
– Implement and improve system level testing across the product lifecycle
– Develop software which can be maintained, improved upon, documented, tested, and reused
– Dive deep on issues at the intersection of hardware and software

A day in the life
The MLA Fleet Operations team was formed to maintain an exceptionally high quality bar for our fleet of advanced machine learning server products. We perfect the customer experience by developing scalable software for rapid incident response times and data visualization as well as diving deep into hardware issues as they arise.

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.

About AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.

Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.

Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.

BASIC 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
– 1+ 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
– Experience with Linux/Unix

PREFERRED QUALIFICATIONS

– Experience building services using AWS products

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.

USA, TX, Austin