Amazon Web Services
Technology
SeniorDeepLearningArchitect,GenerativeAIInnovationCenter
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“Senior Deep Learning Architect, Generative AI Innovation Center at Amazon Web Services. Skills: Generative AI, Deep Learning, Machine Learning, Solution Architecture. Collaborate with AI/ML scientists and architects to research,. Interact with customers directly to understand their business”
What You'll Achieve.
Realize transformational business opportunities; Launch solutions at scale
Industry & Context.
Solve real world problems; Address real-world challenges; Navigate technical or business challenges
What They're Looking For.
Must Have
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, 4+ years of hands on experience with Python to build, train, and evaluate models, 4+ years of technical client engagement experience
Nice to Have
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
What You'll Do.
Collaborate with AI/ML scientists and architects to research
Interact with customers directly to understand their business
Aid customers in implementation of generative AI solutions
Brief customers on adoption patterns and paths to
Guide customers on adoption patterns and paths to
Create and deliver best practice recommendations
Create and deliver tutorials
Create and deliver blog posts
Create and deliver sample code
Create and deliver presentations adapted to technical
Provide customer and market feedback to product and
Design and run experiments
Research new algorithms
Find new ways of optimizing risk
implement and fine tune state-of-the-art solutions
How You'll Work.
Team & Collaboration
Cross-functional teams; Customer interaction
Communication Scope
Client presentations; Executive briefings
Full Job Description
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 en
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