The Machine Learning (ML) Services team within AWS is responsible for setting the strategy and delivering machine learning services across multiple segments and requirements to AWS customers. Today, the team is responsible for multiple customer-facing products such as Amazon SageMaker, Neo, Elastic Inference, Deep Learning AMIs; as well as the core primitives that form the foundation of the entire AWS AI stack, such as ML Frameworks Tensorflow, PyTorch, MXNet, and DL Containers.
In this role, you will be at the center of the ML transformation, joining our team in its Day 1 mission to make machine learning accessible to all software developers and data scientists. You'll use your passion for technology and solving customer problems to develop and drive product plans to develop an exciting offering for customers. As a Principal Product Manager, you will be part of the larger product leadership community at AWS. This community plays a critical role in the broad business planning, working closely with senior management to develop business targets and resource requirements, influences our long-term technical and business strategy, and ultimately enables us to deliver innovative new solutions rapidly. You will be seen as the subject matter expert for your area of focus within Amazon ML.
A successful candidate will bring a passion for technology services, strong business acumen and judgment, desire to have an industry wide impact and ability to work within a fast moving environment in a large company to rapidly deliver value that will have a broad business impact. You will be responsible for understanding customer needs, manage crucial internal stakeholder relationships, provide critical inputs to some of our most strategic technical projects, and have a significant bottom-line impact on our business and competitive position.
Lead Product Definition – Own and drive the customer working backwards strategy, tenets, long-term goals and working backwards documents (press release, FAQ) including customer and market feedback, competitive analysis and business metrics to inform direction.
Define Product Vision – Including all aspects to future roadmap, investment, innovation and experimentation.
Execution of Product Planning and Development – Including customer goals and business requirements for product release, ensuring implementation is aligned with product goals and requirements, and ownership of product positioning.
Lead Product Launch – Own the GTM plan to deliver results that ensure the customer and business goals are met in operational launch plans.
Lead Operations – Including monitoring and response to customer feedback, continuous improvement and business growth
Lead interaction with Technical Team – Including helping the technical team make tradeoffs based on customer requirements, QA/testing of the product.
Influence senior leaders across Amazon and communicate Amazon ML Services vision, strategy, goals, status, and customer impact
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.