Senior Deep Learning Architect, Generative AI Innovation Center

Are you looking to work at the forefront of Machine Learning and AI? Would you be excited to apply Generative AI algorithms to solve real world problems with significant impact? The Generative AI Innovation Center helps AWS customers implement Generative AI solutions and realize transformational business opportunities. This is a team of strategists, scientists, engineers, and architects working step-by-step with customers to build bespoke solutions that harness the power of generative AI. The team helps customers imagine and scope the use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop proof‐of‐concepts, and make plans for launching solutions at scale. 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 empowers 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. BASIC QUALIFICATIONS Bachelor of Science degree in Computer Science, or related technical, math, or scientific field (or equivalent experience)5+ years of experience in designing, building, and/or operating cloud solutions in a production environment 4+ years experience hosting and deploying ML solutions (e.g., for training, fine tuning, and inference)4+ years of hands on experience with Python to build, train, and evaluate models 4+ years of technical client engagement experience PREFERRED QUALIFICATIONS Masters or PhD degree in computer science, or related technical, math, or scientific field 3+ years experience working with deep learning, machine learning, generative AI, or statistics Experience building generative AI applications on AWS using services such as Amazon Bedrock and Amazon SageMaker. Experience communicating across technical and non‐technical audiences, including executive level stakeholders or clients Experience building cloud solutions with AWS #J-18808-Ljbffr