Program Manager II

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Interested in Machine Learning and AI? Our team’s mission is to make machine learning easy, stronger, and universal in the world of Natural Language and Speech. We developed thriving ML services such as Comprehend, Kendra, Lex and Transcribe. We continuously work on adding new services to our portfolio, which address real world problems through research and innovation. We build state-of-the-art services using the latest deep learning techniques and highly scalable distributed systems engineering.
The Program Manager develops, iterates and executes resilient processes to help provide quality data while collaborating with Operations, Science & Development teams. An ideal candidate is analytical, autonomous, and cross functionally collaborative with effective communication skills. They are accountable towards organizational goals and work backwards from customers, stakeholders and dependent teams to successfully deliver results in a fast-paced and dynamic business environment

Key responsibilities of the role include (not limited to):
1. Execute stakeholder engagement processes focused on delivering quality training data for Amazon AI teams.
2. Drive and facilitate complex projects focusing on results and measuring attainment of outcomes.
3. Assist with the definition and design of tools, standard operating procedures and processes.
4. Design scaled processes by gathering functional requirements, identifying resources needed, and defining milestones and launch schedule to ensure timely and successful delivery of the projects.
4. Influence stakeholders (including Data Science, Development teams & Support function) outside your direct area of responsibility to ensure delivery. Identify and mitigate risks, and remove roadblocks within projects. Drive accountability from stakeholders for progress on key program actions through active engagement and escalation.
5. Conduct effective meetings (business and program reviews) and able to dive deeply into details as easily as convey high-level plans with clear and concise verbal and written communication. Transform raw thoughts into clear documentation and requirements (e.g., project charter, statement of work, responsibility matrix, functional requirements, implementation approach, reporting, etc.).
6. Audit activities impacting data quality and define processes to address root cause.

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 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
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.

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