Senior Applied Scientist, Amazon

• PhD degree in computer science, engineering, mathematics, operations research, or in a highly quantitative field plus 5 years of relevant experience, or Master’s degree plus 10 years of relevant work experience
• 5+ years of hands on experience with Python to build, train, and evaluate models
• 5+ years of hands on experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing
• 2+ years demonstrated experience with Large Language Model (LLM) and Foundational Model post-training, continual pre-training, fine-tuning, or reinforcement learning techniques
• Scientific publication track record at top-tier AI/ML/NLP conferences or journals

Desirable

• 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 bespoke use cases that will create the greatest value for their businesses, define paths to navigate technical or business challenges, develop and optimize models to power their solutions, 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 Applied Scientists capable of using GenAI and other techniques to design, evangelize, and implement state-of-the-art solutions for never-before-solved problems
• 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
• Help customers optimize their solutions through approaches such as model selection, training or tuning, right-sizing, distillation, and hardware optimization
• Provide customer and market feedback to product and engineering teams to help define product direction