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Key job responsibilities
Every day will bring new and exciting challenges on the job while you:
- Make recommendations on AI architecture, security, cost optimization, and operational excellence- Complete analysis and present periodic reviews of AI workload performance- Foster an ecosystem where AI and humans progress together through knowledge sharingDiverse Experiences
AWS values diverse experiences. Even if you do not meet all of the preferred 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.
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
- Master's degree in Computer Science, Artificial Intelligence, Machine Learning or related technical field
- Deep understanding of Generative AI fundamentals, Large Language Models, and core AI/ML concepts
- Strong theoretical foundation in AI technologies and their underlying principles
- Strong empirical reasoning skills with ability to formulate theories, make predictions, validate and refine solutions
- PhD in Computer Science, Artificial Intelligence, Machine Learning or related field
- Demonstrated ability to build systematic knowledge frameworks across technology stacks
- Experience with implementing enterprise-scale AI/ML solutions
- Experience with AWS core services across Compute, Storage, Database, and Networking
- Knowledge of cloud architecture patterns and distributed systems, cloud security principles and compliance frameworks
- Experience with container technologies and serverless architectures, modern software development practices and DevOps
- Excellence in stakeholder management and technical communication
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