Amazon is 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.
Requirements
- Deep technical experience working with technologies related to large language models including LLM architectures, model evaluation, and fine-tuning techniques
- Proficient with design, deployment, and evaluation of foundation models - including evaluation dataset design, metric design, implementation, failure analysis
- Hands on experience with both AI Frameworks (e.g. Strands, LangGraph, CrewAI, DSPy) and model customization tools including PyTorch, TensorBoard, MLFlow/W&B, Bedrock, and SageMaker
- Experience with optimizing ML workloads using Model compression, distillation, pruning, sparsification, quantization, Transformers based algorithms like FlashAttention, PagedAttention, Speculative decoding, Distributed training/inference optimization, Hardware-informed efficient model architecture
- Experience with open source frameworks for building applications powered by language models like LangChain, LlamaIndex
- Experience with design, deployment, and evaluation of LLM-powered agents and tools and orchestration approaches
- Experience with AWS technologies like SageMaker, Step Functions, OpenSearch, PgVector, S3, IAM, Cognito, EC2, Glue, & EMR
Responsibilities
- Customer Advisor- Implement, and deploy state of the art machine learning solutions under Gen AI. You will build prototypes, PoCs, and explore new solutions. You will interact closely with our customers.
- Thought Leadership – Evangelize AWS GenAI services and share best practices through forums such as AWS blogs, white-papers, reference architectures and public-speaking events such as AWS Summit, AWS re:Invent, etc.
- Ensure success in designing, building and migrating applications, software, and services with Amazon Nova FM's, AWS Bedrock, and other AWS GenAI capabilities.
- Interact with customers directly to understand their business problems and help them implement durable GenAI systems.
- Drive evaluation strategy, metric design, and evaluation data design for real-world use cases
- Drive deep architectural discussions and design exercises to create solutions built with Amazon Nova FM's
- Author and contribute to AWS customer-facing publications such as whitepapers, workshops, demos and proof of concepts.
Other
- Master's degree in a quantitative field such as 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+ year experience working with technologies related to large language models including LLM architectures and model evaluation
- 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
- Ability to communicate clearly and compellingly at all levels of the company
