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Amazon

Senior Generative AI Data Scientist, Amazon SageMaker

Amazon, Seattle, Washington, us, 98127


Senior Generative AI Data Scientist, Amazon SageMaker

Are you passionate about Generative AI (GenAI)? Do you want to help define the future of Go to Market (GTM) at AWS using generative AI? In this role, you will help some of our largest customers build and deploy GenAI enabled applications using Amazon SageMaker, fine tune and build Generative AI models, and help enterprise customers leverage these models to power end applications. You will engage with AWS product owners to influence product direction and help our customers tap into new markets by utilizing GenAI along with AWS Services. AWS is looking for a Generative AI Data Scientist, who will be the Subject Matter Expert (SME) for helping customers in designing solutions that leverage our Generative AI services. You will interact with customers directly to understand the business problem, aid them in implementation of generative AI solutions, deliver briefing and deep dive sessions to customers and guide them on adoption patterns for generative AI. As part of the Generative AI Worldwide Specialist organization, you will work closely with other Data Scientists and Machine Learning Architects to enable large-scale customer use cases and drive the adoption of Amazon Web Services for GenAI services. You will develop white papers, blogs, reference implementations, and presentations to enable customers and partners to fully leverage Generative AI services on Amazon Web Services. You must have deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, adapters, pre-training and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches. You must have experience with embedding model fine tuning and retrieval method evaluation approaches. Candidates must have great communication skills and be very technical, with the ability to impress Amazon Web Services customers at any level, from executive to developer. Previous experience with Amazon Web Services is desired but not required, provided you have experience building large scale solutions. You will get the opportunity to work directly with senior ML engineers and Data Scientists at customers, partners and Amazon Web Services service teams, influencing their roadmaps and driving innovation. Key job responsibilities Customer Advisor - Implement, and deploy state of the art machine learning algorithms under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers and with the academic community. Thought Leadership - Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events. Partner with Data Scientists, SAs, Sales, Business Development and the Generative AI Service teams to accelerate customer adoption and provide guidance on their customer engagements. Act as a technical liaison between customers and the AWS Generative AI services teams to provide customer driven product improvement feedback. Develop and support an AWS internal community of ML related subject matter experts worldwide. Create field enablement materials for the broader technical population, to help them understand how to integrate AWS GenAI solutions into customer architectures. Minimum Requirements 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience. 5+ years of data scientist experience. Experience with statistical models e.g. multinomial logistic regression. 5+ years of experience with Python to analyze datasets, train, evaluate, deploy, and optimize models. 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience. Experience managing data pipelines. Experience as a leader and mentor on a data science team. Experience with open source frameworks for building applications powered by language models like LangChain, LlamaIndex. Design, develop, and optimize high-quality prompts and templates that guide the behavior and responses of LLM. Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches. Customer facing skills to represent AWS well within the customer’s environment and drive discussions with senior personnel regarding trade-offs, best practices, and risk mitigation. Demonstrated ability to think strategically about business, product, and technical challenges in an enterprise environment. Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. 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 https://amazon.jobs/content/en/how-we-hire/accommodations for more information.

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