Applied Scientist, Automated Reasoning

About This Role

This Applied Scientist role in AWS Automated Reasoning focuses on developing and applying cutting-edge formal methods, automated reasoning techniques, and neurosymbolic approaches to ensure the security, reliability, and correctness of Amazon/AWS services and customer applications. The position offers a unique opportunity to contribute to a fast-growing segment of the business, shaping technology, product, and business outcomes, while making a significant impact on customers.

Responsibilities

• Design and implement algorithms and formal methods for automated reasoning, including constraint solving, model checking, static analysis, theorem proving, and program synthesis to verify the correctness, security, and reliability of computing systems
• Solve large or significantly complex problems requiring deep knowledge and scientific innovation; own strategic problem solving and lead the design, implementation, and delivery of solutions with long-term quantifiable impact
• Develop new decision procedures, heuristics, and search strategies that improve the scalability and accuracy of verification tools; build and deploy production-grade automated reasoning systems at Amazon scale
• Explore and apply generative AI and machine learning techniques to enhance automated reasoning capabilities, including learning-based heuristics for search and optimization, neural approaches to symbolic reasoning, and methods for verifying the correctness of AI-generated code
• Develop automated reasoning techniques for generative AI and agentic coding systems, including methods for ensuring the safety and alignment of autonomous software agents and applying formal guarantees to large language model outputs
• Conduct original research and publish findings in peer-reviewed venues
• Work with customer teams to understand their software and required properties; identify tools and methods capable of addressing verification needs, including novel analysis capabilities
• Provide cross-organizational technical influence, increasing productivity and effectiveness by sharing deep knowledge and experience; collaborate with partner teams to translate verification capabilities into production systems
• Mentor scientists and engineers on formal methods, neurosymbolic techniques, and best practices for building reliable automated reasoning systems; assist in career development of others

Requirements

• PhD or equivalent research experience
• Experience in any of the following areas: mathematical logic, formal verification, satisfiability solving (e.g., SAT/SMT), mechanical theorem proving, model checking, or program analysis

Nice to have:

• Experience in professional software development
• Experience applying formal methods or automated reasoning to real-world software, security, or systems problems