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Manager of Applied Science, Generative AI Solutions
2 months ago
Job ID: | Amazon Web Services Australia Pty Ltd - D81
Amazon has established the Generative AI Innovation Center (GAIIC) to empower AWS clients in leveraging Generative AI for addressing business challenges and fostering innovation within their organizations.
GAIIC offers a dynamic environment for innovation, contributing to transformative projects and technologies that are implemented across various platforms. As an Applied Science Manager at GAIIC, you will collaborate with both technology and business teams to create novel GenAI solutions that enhance customer satisfaction. Your role will involve leading a team of data scientists, research scientists, deep learning architects, and machine learning engineers to develop generative AI models and frameworks, delivering cutting-edge solutions to meet client needs.
Your team will engage with extensive datasets, including text, images, and diverse data types, to tackle real-world challenges.
The ideal candidate will possess a blend of technical expertise and customer engagement skills, enabling you to serve as the technical representative of AWS within our ecosystem and directly with clients. You will facilitate discussions with senior technical and management personnel, and your technical background will empower you to guide data scientists and software developers effectively.
Furthermore, the successful candidate will demonstrate strategic thinking regarding business, product, and technical matters. A key aspect of this role is being an exceptional technical team leader, adept at recruiting, developing, and retaining top-tier technical talent.
About the Team
Diverse Experiences:
AWS values diverse experiences. We encourage candidates from all backgrounds to apply, regardless of whether they meet every qualification listed in the job description. If your career path is non-traditional or includes alternative experiences, we welcome your application.
Why AWS?
Amazon Web Services (AWS) is the leading and most widely adopted cloud platform globally. We have been at the forefront of cloud computing innovation, earning the trust of customers ranging from successful startups to Fortune 500 companies, thanks to our comprehensive suite of products and services.
Inclusive Team Culture:
At AWS, we foster a culture of learning and curiosity. Our employee-led affinity groups promote inclusion and celebrate our differences. Regular events and learning opportunities, such as our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, encourage us to embrace our uniqueness.
Mentorship & Career Growth:
We are committed to raising our performance standards as we aim to be Earth's Best Employer. You will find ample knowledge-sharing, mentorship, and career development resources to help you grow as a well-rounded professional.
Work/Life Balance:
We prioritize work-life harmony. Achieving success in your career should not come at the expense of personal sacrifices. Flexible work hours and arrangements are integral to our culture, allowing us to thrive both at work and at home.
- 3+ years of experience managing scientists or machine learning engineers
- Proficiency in ML, NLP, Information Retrieval, and Analytics
- Proven experience in directly overseeing scientists or machine learning engineers
- Experience in developing machine learning models or algorithms for business applications
- Background in building complex software systems, particularly those involving deep learning, machine learning, and computer vision, successfully delivered to clients
Acknowledgement of Country:
In the spirit of reconciliation, Amazon acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea, and community. We pay our respects to their elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
IDE Statement:
Amazon is dedicated to fostering a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, national origin, gender, gender identity, sexual orientation, disability, age, or other legally protected attributes.
