SageMaker Training Jobs is looking for an L5 SDE!
This is a rare opportunity to join the SageMaker Training Jobs team, which lies at the very core of SageMaker. Learn more at https://docs.aws.amazon.com/sagemaker/latest/dg/how-it-works-training.html.
You will be responsible for building and maintaining mission-critical systems in our best-in-class machine learning platform, and scale those systems to support training jobs that run on tens of thousands of machines with less than 0.1% failure rate.
You will constantly experiment with new technologies and ideas in order to innovate on our platform and help ensure SageMaker remains best-in-class.
You will be expected to perform at the highest levels of engineering and operational excellence: building highly resilient and scalable systems, writing clear and effective documents, actively contribute to discussions on technical direction and strategy, and raise the bar on all fronts.
Most importantly, you will get to work with a team of highly talented engineers who have all answered the call above and strive for new heights every day.
About Amazon SageMaker
Amazon SageMaker is a fully managed Machine Learning platform that makes it easy to build ML models, manage them, and integrate them with custom applications for online predictions. SageMaker takes away the heavy-lifting normally associated with large-scale Machine Learning implementations, so that developers and scientists can focus on the truly creative work of modeling and solving the business problem at hand.
SageMaker has grown at a rapid pace and the growth rate is only accelerating. There are new services being developed, and novel capabilities being added to existing services based on a tight feedback loop with the customers. SageMaker is currently used by small, medium, and large businesses all across the world, including some of the biggest names in industry. SageMaker is also launching the new and existing services in more regions than ever before. The team plans to launch in many new regions over the next 2 years.
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.
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. 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.BASIC QUALIFICATIONS
- 2+ years of non-internship professional software development experience
- Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
- 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
- 1+ years of experience building distributed systems with AWS technologies
- Top-tier verbal and written communication skills
- AWS developers preferred
- Programming experience with Go or systems programming experience
- Project leadership experience
- Basic understanding of machine learning concepts and terminology
Amazon is committed to a diverse and inclusive workforce. Amazon is an equal opportunity employer and does not discriminate on the basis of race, ethnicity, 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
Software and Programming