Amazon
Sr. Applied AI - Data Scientist, Amazon Nova
Amazon, San Francisco, California, United States, 94199
Sr. Applied AI - Data Scientist, Amazon Nova
Join to apply for the Sr. Applied AI - Data Scientist, Amazon Nova role at Amazon Web Services (AWS). Overview
Are you an AI-focused data scientist who wants to think fast, dive deep, and build? We are seeking a data scientist to join the Amazon Nova Solutions team to work with Foundation Model (FM) teams alongside internal and external Generative AI customers to customize foundation models and build the applications of the future. You will be the voice of the builder, working alongside Amazon businesses to develop GenAI solutions that deliver immediate business value and shape the future of customer experience. You will help customers understand best practices and develop new patterns as you encounter new problem spaces. You will provide insights to product, science, and engineering on how customers build with our FM services and how we can improve. You will be empowered to invent on behalf of our customers and advocate for their needs throughout design, build, and launch of next-gen FM capabilities. You must have deep technical experience with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of foundation models including evaluation dataset design, metric design, implementation, and failure analysis. Ideal candidates have hands-on experience with AI frameworks and model customization tools (e.g., PyTorch, TensorBoard, MLFlow/W&B, Bedrock, SageMaker). This position has high visibility, so you will need to communicate clearly and compellingly at all levels. You will also be responsible for measuring business impact by diving into metrics and customer inputs. A positive attitude, strong work ethic, and ability to move fast and iterate are important. Key responsibilities
Customer Advisor Implement and deploy state-of-the-art ML solutions under Gen AI. Build prototypes, PoCs, and explore new solutions. Interact closely with customers. Thought Leadership Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white papers, reference architectures, and public events (AWS Summit, AWS re:Invent). Ensure success in designing, building, and migrating applications and services with Amazon Nova FM's, AWS Bedrock, and other GenAI capabilities. Interact with customers to understand business problems and help implement durable GenAI systems. Educate customers on the value proposition of the Amazon Nova FM ecosystem and showcase the art of the possible. Drive evaluation strategy, metric design, and evaluation data design for real-world use cases. Lead architectural discussions and design exercises to create solutions built with Amazon Nova FM's. Author and contribute to AWS customer-facing publications (whitepapers, workshops, demos, proofs of concept). Build deep relationships with customer engineering, product, and science leaders. About The Team
Amazon Nova Applied AI Solutions Team bridges Foundation Model science, engineering, and product teams with internal Amazon teams using these models to deliver business value. We help customers build Generative AI applications and apply learnings to improve Foundation Models daily. Basic Qualifications
Master's degree in statistics, mathematics, data science, business analytics, engineering, or computer science. 5+ years of experience in end-to-end technical architecture, design, deployment, and operations for Generative AI/ML platforms and applications. 3+ years of experience with technologies related to large language models, including LLM architectures and model evaluation. Experience in design/implementation/consulting for Machine Learning/AI/Deep Learning solutions. Experience in relevant technology domains (software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics). Preferred Qualifications
Experience optimizing ML workloads with model compression, distillation, pruning, quantization, and transformer-based optimization (e.g., FlashAttention, PagedAttention, Speculative decoding) and distributed training/inference optimization. Experience with open-source frameworks for LLM-powered applications (e.g., LangChain, LlamaIndex). Ability to design, develop, and optimize prompts and templates for LLM behavior. Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches; strong customer-facing skills to engage with senior stakeholders and discuss trade-offs, best practices, and risk mitigation. Experience with AWS technologies like SageMaker, Step Functions, OpenSearch, PgVector, S3, IAM, Cognito, EC2, Glue, and EMR. Experience with Container Platforms (Docker, Kubernetes/Fargate). Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. The position will remain posted until filled. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you need a workplace accommodation during the application process, please visit amazon.jobs accommodations for more information. #J-18808-Ljbffr
Join to apply for the Sr. Applied AI - Data Scientist, Amazon Nova role at Amazon Web Services (AWS). Overview
Are you an AI-focused data scientist who wants to think fast, dive deep, and build? We are seeking a data scientist to join the Amazon Nova Solutions team to work with Foundation Model (FM) teams alongside internal and external Generative AI customers to customize foundation models and build the applications of the future. You will be the voice of the builder, working alongside Amazon businesses to develop GenAI solutions that deliver immediate business value and shape the future of customer experience. You will help customers understand best practices and develop new patterns as you encounter new problem spaces. You will provide insights to product, science, and engineering on how customers build with our FM services and how we can improve. You will be empowered to invent on behalf of our customers and advocate for their needs throughout design, build, and launch of next-gen FM capabilities. You must have deep technical experience with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques. You should be proficient with design, deployment, and evaluation of foundation models including evaluation dataset design, metric design, implementation, and failure analysis. Ideal candidates have hands-on experience with AI frameworks and model customization tools (e.g., PyTorch, TensorBoard, MLFlow/W&B, Bedrock, SageMaker). This position has high visibility, so you will need to communicate clearly and compellingly at all levels. You will also be responsible for measuring business impact by diving into metrics and customer inputs. A positive attitude, strong work ethic, and ability to move fast and iterate are important. Key responsibilities
Customer Advisor Implement and deploy state-of-the-art ML solutions under Gen AI. Build prototypes, PoCs, and explore new solutions. Interact closely with customers. Thought Leadership Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white papers, reference architectures, and public events (AWS Summit, AWS re:Invent). Ensure success in designing, building, and migrating applications and services with Amazon Nova FM's, AWS Bedrock, and other GenAI capabilities. Interact with customers to understand business problems and help implement durable GenAI systems. Educate customers on the value proposition of the Amazon Nova FM ecosystem and showcase the art of the possible. Drive evaluation strategy, metric design, and evaluation data design for real-world use cases. Lead architectural discussions and design exercises to create solutions built with Amazon Nova FM's. Author and contribute to AWS customer-facing publications (whitepapers, workshops, demos, proofs of concept). Build deep relationships with customer engineering, product, and science leaders. About The Team
Amazon Nova Applied AI Solutions Team bridges Foundation Model science, engineering, and product teams with internal Amazon teams using these models to deliver business value. We help customers build Generative AI applications and apply learnings to improve Foundation Models daily. Basic Qualifications
Master's degree in statistics, mathematics, data science, business analytics, engineering, or computer science. 5+ years of experience in end-to-end technical architecture, design, deployment, and operations for Generative AI/ML platforms and applications. 3+ years of experience with technologies related to large language models, including LLM architectures and model evaluation. Experience in design/implementation/consulting for Machine Learning/AI/Deep Learning solutions. Experience in relevant technology domains (software development, cloud computing, systems engineering, infrastructure, security, networking, data & analytics). Preferred Qualifications
Experience optimizing ML workloads with model compression, distillation, pruning, quantization, and transformer-based optimization (e.g., FlashAttention, PagedAttention, Speculative decoding) and distributed training/inference optimization. Experience with open-source frameworks for LLM-powered applications (e.g., LangChain, LlamaIndex). Ability to design, develop, and optimize prompts and templates for LLM behavior. Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches; strong customer-facing skills to engage with senior stakeholders and discuss trade-offs, best practices, and risk mitigation. Experience with AWS technologies like SageMaker, Step Functions, OpenSearch, PgVector, S3, IAM, Cognito, EC2, Glue, and EMR. Experience with Container Platforms (Docker, Kubernetes/Fargate). Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status. The position will remain posted until filled. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you need a workplace accommodation during the application process, please visit amazon.jobs accommodations for more information. #J-18808-Ljbffr