The Generative AI Innovation Center at AWS helps AWS customers accelerate the use of Generative AI and realize transformational business opportunities. This is a cross-functional team of ML scientists, engineers, architects, and strategists working step-by-step with customers to build bespoke solutions that harness the power of generative AI.
As a Deep Learning Architect, you'll partner with technology and business teams to build solutions that surprise and delight our customers. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.
We’re looking for Engineers and Architects capable of using generative AI and other ML techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems.
AWS Sales, Marketing, and Global Services (SMGS) is responsible for driving revenue, adoption, and growth from the largest and fastest growing small- and mid-market accounts to enterprise-level customers including public sector. The AWS Global Support team interacts with leading companies and believes that world-class support is critical to customer success. AWS Support also partners with a global list of customers that are building mission-critical applications on top of AWS services.
Key job responsibilities
- Collaborate with ML scientist and engineers to research, design and develop cutting-edge generative AI algorithms to address real-world challenges
- Work across customer engagement to understand what adoption patterns for generative AI are working and rapidly share them across teams and leadership
- Interact with customers directly to understand the business problem, help and aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide customer on adoption patterns and productionization paths for generative AI
- Create and deliver reusable technical assets that help to accelerate the adoption of generative AI on AWS platform
- Create and deliver best practice recommendations, tutorials, blog posts, sample code, and presentations adapted to technical, business, and executive stakeholder
- Provide customer and market feedback to Product and Engineering teams to help define product direction
About the team
GenAIIC provides opportunities to innovate in a fast-paced organization that contributes to game-changing projects and technologies that get deployed on devices and in the cloud. As a Data Science Manager in GenAIIC, you'll partner with technology and business teams to build new generative AI solutions that delight our customers. You will be responsible for directing a team of data/research/applied scientists, deep learning architects, and ML engineers to build generative AI models and pipelines, and deliver state-of-the-art solutions to customer’s business and mission problems.
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS?
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture
Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth
We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance
We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
BASIC QUALIFICATIONS
- Bachelor’s degree in computer science, engineering, mathematics or equivalent
- Experience in design, implementation, or consulting in applications and infrastructures
- Experience architecting or deploying Cloud/Virtualization solutions in enterprise customers
- Proven knowledge of deep learning and experience hosting and deploying ML solutions (e.g., for training, tuning, and inferences)
- Scientific thinking and the ability to invent, a track record of thought leadership and contributions that have advanced the field
PREFERRED QUALIFICATIONS
- MSc degree in computer science, engineering, mathematics or equivalent
- Proven knowledge of Generative AI and hands-on experience of building applications with large foundation models
- Proven knowledge of AWS platform and tools
- Hands-on experience of building ML solutions on AWS
- Experience in professional software development
