Senior Deep Learning Architect, Generative AI Innovation Center
6 hours ago
The GenAI Innovation Center team provides guidance on best practices for applying generative AI responsibly and cost efficiently. You will work directly with customers and innovate in a fast-paced organization that contributes to game-changing projects and technologies.
You will design and run experiments, research new algorithms, and find new ways of optimizing risk, profitability, and customer experience.
We're looking for top architects, system and software engineers capable of using ML, Generative AI and other techniques to design, evangelize, implement and fine tune state-of-the- art solutions for never-before-solved problems.
As a Deep Learning Architect, you will
- Collaborate with AI/ML scientists and architects to research, design, develop, and evaluate generative AI solutions to address real-world challenges
- Interact with customers directly to understand their business problems, aid them in implementation of generative AI solutions, brief customers and guide them on adoption patterns and paths to production
- 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
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 (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.
- Bachelor's degree in Computer Science or a related field
- 5+ years of cloud based solution (AWS or equivalent), system, network and operating system experience
- Experience managing and deploying ML products
- 4+ years of building machine learning models for business application experience
- 5+ years of leading and delivering enterprise-level IT engagements experience
- Master's degree in computer science, computer engineering, or related field, or PhD
- 3+ years of machine learning, statistical modeling, data mining, and analytics techniques experience
- 8+ years of leading development of applications backed by AWS services or using other cloud based technologies and services experience
- Experience communicating across technical and non-technical audiences, including executive level stakeholders or clients
- Experience architecting/operating solutions built on AWS
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit for more information. If the country/region you're applying in isn't listed, please contact your Recruiting Partner.
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