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AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the 8 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.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 BalanceKey job responsibilities
• Ensure success in designing, building and migrating applications, software, and services on the AWS platform.
• Interact with customers directly to understand business challenges, help and aid them in implementation of their ML ecosystem
• Educate customers on the value proposition of AWS and showcase the art of possible.
• Participate in deep architectural discussions and design exercises to create world-class solutions built on AWS while ensuring solutions are designed for successful deployment in the cloud.
• Author and contribute to AWS customer-facing publications such as whitepapers, workshops, demos and proof of concepts.
• Build deep relationships with senior technical individuals within customers to enable them to be cloud advocates.
• Capture and share best-practice knowledge amongst the AWS solutions architect community.
• Work with AWS Service teams in synthesizing customer and market feedback to evolve the AWS Services roadmap
A day in the life
The ideal candidate:
• Has deep expertise in AI/ML (specifically Generative AI).
• Has prior experience working as a Solution Architect.
• Is deeply technical and keeps their technical skills honed. Often helps teach new skills to others.
• Has a combination of design and architecture knowledge with development capability (comfortable on the white-board and also on the keyboard).
• Thrives in ambiguous situations and can bring focus and help deliver results.
• Communicates efficiently and effectively with both technical and non-technical audiences
• Is great fun to work with.
- 10+ years of specific technology domain areas (e.g. software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics) experience
- Bachelor's degree in computer science, engineering, mathematics or equivalent
- 5+ years of design, implementation, or consulting experience in AI/ML (1+ in Generative AI specifically)
- Experience contributing to the system design (architecture, design patterns, reliability and scaling) of new and current GenAI systems.
- Masters or PhD degree in computer science, or related STEM field
- 5+ Years of experience working with Machine Learning and Data Science communities.
- 3+ years of experience working with AWS ML technologies.
- Strong working knowledge of deep learning, machine learning and statistics
- Deep knowledge of software development tools and methodologies and active, hands-on coding and AI/ML application design experience
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