About the job
Amazon is seeking an Applied Scientist II to join our team and drive innovation in Generative AI and Large Language Model (LLM) applications. In this role, you will design, develop, and deploy AI solutions that directly impact millions of customers and transform how Amazon operates at scale. You'll work with state-of-the-art technologies including foundation models, prompt engineering, retrieval-augmented generation (RAG), and fine-tuning techniques to solve complex business problems.
Responsibilities
Model Development & Innovation: Design and implement novel GenAI/LLM solutions using foundation models (e.g., Claude, GPT, LLaMA) and AWS services including Amazon Bedrock, SageMaker, and other AWS AI/ML tools
Research & Experimentation: Conduct applied research to advance the state-of-the-art in LLM applications, including prompt engineering, few-shot learning, fine-tuning, and model evaluation
Production Deployment: Build scalable, production-ready AI systems that serve millions of requests with high reliability, low latency, and cost efficiency
Cross-Functional Collaboration: Partner with product managers, engineers, and business stakeholders to translate business requirements into technical solutions and drive measurable impact
Technical Leadership: Mentor junior scientists, contribute to technical strategy, and establish best practices for GenAI development across the organization
Evaluation & Metrics: Design rigorous evaluation frameworks to measure model performance, bias, safety, and business impact
Documentation & Communication: Publish technical papers, create detailed documentation, and present findings to both technical and non-technical audiences
Qualifications
Minimum
3+ years of building models for business application experience
PhD, or Master's degree and 4+ years of CS, CE, ML or related field experience
Experience in patents or publications at top-tier peer-reviewed conferences or journals
Experience programming in Java, C++, Python or related language
Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
Preferred
PhD in computer science, machine learning, engineering, or related fields
2+ years of hands-on experience with foundation models and LLM applications (prompt engineering, RAG, fine-tuning, RLHF, Transformer models, and AI Agents)
Experience with AWS AI/ML services (Amazon Bedrock, SageMaker, Lambda, etc.)
Publications in top-tier conferences (NeurIPS, ICML, ACL, EMNLP, ICLR, COLM, etc.)
Experience with model optimization techniques (quantization, distillation, efficient inference)
Knowledge of responsible AI practices including bias detection, fairness, and safety evaluation