At Amazon Elastic Kubernetes Service (EKS) , we are building a core set of services that allow our customers to create and use Kubernetes at scale. You will be part of an exceptional team moving the needle towards making containers as the next generation compute platform. This is an opportunity to operate and engineer on a massive scale, and to gain top-notch experience in cloud computing.
As an ML OPS Engineer in Amazon Elastic Kubernetes Service (EKS) compute team, you will help make EKS the most reliable place to run AI/ML workloads on Kubernetes at massive scale (10,000 or more nodes per cluster). We are looking for engineers to help build our strong product roadmap and who have or want to develop deep expertise in Kubernetes data plane ecosystem.
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.
This position involves on-call responsibilities, typically for one week every two months. We don’t like getting paged in the middle of the night or on the weekend, so we work to ensure that our systems are fault tolerant. When we do get paged, we work together to resolve the root cause so that we don’t get paged for the same issue twice.
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. 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 based on what will help each team member develop into a better-rounded engineer and enable them to take on more complex tasks in the future.
Key job responsibilities
- Tune Amazon EKS accelerated machine images (AMI) to be best in class for AI/ML workloads
- Write test suites that accurately represent Kubernetes workloads
- Design and build CI/CD pipelines that perform functional, load tests and security scans for EKS GPU machine images
A day in the life
- Collaborate with peers over design approaches
- Write critical path code and review your peer's code
- Investigate issues and improve SLOs when oncall
- Attend daily standups
We are open to hiring candidates to work out of one of the following locations:
Seattle, WA, USA
BASIC QUALIFICATIONS- 3 years of programming with at least one modern language such as C , C#, Java, Python, Golang, PowerShell, Ruby experience
- 4 years of non-internship professional software development experience
- 2 years of designing or architecting (design patterns, reliability and scaling) of new and existing systems experience
- Experience leading the design, build and deployment of complex and performant (reliable and scalable) software solutions in production
PREFERRED QUALIFICATIONS- Knowledge of engineering practices and patterns for the full software/hardware/networks development life cycle, including coding standards, code reviews, source control management, build processes, testing, certification, and livesite operations
- Experience taking a leading role in building complex software or computing infrastructure that has been successfully delivered to customers
- Hands on experience with Kubernetes, Nvidia, CUDA
- Ability to improve performance of ML workloads on AWS (tuning and configuration)
- Work with customers independently
- Hands on experience running large training and inference workloads
- Experience with machine learning frameworks i.e: PyTorch, TensorFlow 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 $121,000/year in our lowest geographic market up to $235,200/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.

About the Company:
Amazon.com Services LLC