- Bachelor's degree in Computer Science, Computer Engineering or equivalent combination of technical education and experience
- 7+ years of management experience with at least 2+ years of experience managing managers.
- 8+ years experience building distributed systems
- 5+ years experience in preparing quality metrics and effectively engaging with stakeholders to set and drive quality goals
- Experience with modern programming languages (Java, C#, Python) and open-source technologies.
Interested in Machine Learning? 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 https://aws.amazon.com/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.
As a Senior Manager, you will own the innovation in the space of ML Platforms, building compelling functionality for the Amazon SageMaker Service. You will be responsible for leading a team of engineers and first line managers in design, development, test, and deployment of distributed systems and big data solutions. A successful candidate will have an established background in developing distributed systems, a strong technical ability, excellent project management skills, great communication skills, and a motivation to achieve results in a fast paced environment.
About the domain -
ML customers work with petabytes of raw data and they expect a managed data platform to support multiple data flows that can read and write data concurrently while ensuring data integrity with the strongest level of isolation.
As the engineering leader for SageMaker data lifecycle system, you will be responsible to lead the design and development of a platform to serve the most demanding ML data processing use cases for our customers.
Some such platform capabilities include
1. Ability to process vast raw data leveraging AWS technologies such as EMR
2. Support for efficient batch processing workflows as well as near-real-time processing of streaming data
3. Ability to easily track, reproduce, or revert back to a previously computed version of data set (time travel)
4. State of the art big data visualization toolset on SageMaker platform
SageMaker data lifecycle system will need to work seamlessly with the rest of the SageMaker ecosystem, as well as customers' ETL pipeline, while providing the highest level of data privacy and operational excellence that customers expect from AWS services.
Come join the SageMaker team to help build this new and exciting data lifecycle platform, tailored to AI/ML customers, from the ground up.
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 we 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.
- PhD in computer science or
- 15+ years of experience in the Software Development Industry
- 5+ years of experience in managing managers
- Experience with large scale distributed systems
- Experience with Machine Learning
- Leading cross functional teams with UX and Front End Developers
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.