Overview
This role sits within Amazon's Automated Reasoning and Formal Verification research horizon. Shape the Future of Cloud Computing. Are you a graduate student passionate about Automated Reasoning and its real-world applications? Join our team of innovators and embark on a journey to revolutionize cloud computing through innovative automated reasoning techniques. Our tools are called billions of times daily, powering the backbone of Amazon's products and services. We are changing the way computer systems are developed and operated, raising the bar for security, durability, availability, and quality. Applied Scientists in Automated Reasoning develop and apply formal methods, automated reasoning techniques, and neurosymbolic approaches to ensure the security, reliability, and correctness of Amazon and AWS services and customer applications. Application areas span cloud infrastructure verifica
Complete research opportunity details
Full Job Description
This role sits within Amazon's Automated Reasoning and Formal Verification research horizon.
Shape the Future of Cloud Computing. Are you a graduate student passionate about Automated Reasoning and its real-world applications? Join our team of innovators and embark on a journey to revolutionize cloud computing through innovative automated reasoning techniques. Our tools are called billions of times daily, powering the backbone of Amazon's products and services. We are changing the way computer systems are developed and operated, raising the bar for security, durability, availability, and quality.
Applied Scientists in Automated Reasoning develop and apply formal methods, automated reasoning techniques, and neurosymbolic approaches to ensure the security, reliability, and correctness of Amazon and AWS services and customer applications. Application areas span cloud infrastructure verification, cryptographic assurance, AI safety, and formal guarantees for generative AI systems. Methods range from interactive theorem proving and constraint solving to neuro-inspired proof search.
As an Applied Science Intern, you will have the opportunity to work alongside our scientists and contribute to projects. From distributed proof search and SAT/SMT solvers to program analysis, synthesis, and verification, you will tackle complex challenges at the intersection of theory and practice.
Amazon has positions available for Automated Reasoning Applied Science Internships in, but not limited to, Arlington, VA; Boston, MA; New York, NY; Portland, OR; Santa Clara, CA; Seattle, WA; Austin, TX; Cambridge, UK.
Key job responsibilities We are particularly interested in candidates with expertise in: Theorem Proving, Boolean Satisfiability Solvers, Bounded Model Checking, Deductive Verification, Programming/Scripting Languages, Abstract Interpretation, Automated Reasoning, Static/Program Analysis, Program Synthesis.
Contribute to the design and implementation of algorithms and formal methods for automated reasoning, including constraint solving, model checking, static analysis, theorem proving, and program synthesis, within a guided research framework.
Explore and apply generative AI and machine learning techniques to enhance automated reasoning, including learning-based heuristics for search, neural approaches to symbolic reasoning, and methods for verifying the correctness of AI-generated code.
Contribute to automated reasoning techniques for generative AI and agentic coding systems, including methods that apply formal guarantees to large language model outputs.
Contribute to the scientific community through publications at peer-reviewed conferences and journals.
Leverage AI-powered tools where applicable to accelerate research, experimentation, and prototyping. Critically review and validate outputs from AI tools and automated systems.
The ideal intern must have the ability to communicate research findings clearly to diverse audiences.
Basic Qualifications
- Are enrolled in a PhD
- Can relocate to where the internship is based
- Work 40 hours/week minimum and commit to 12 week internship minimum
- Experience programming in Python, and where applicable, C++, Haskell, or Lean
- Experience in one or more of the following: mathematical logic, formal verification, satisfiability solving (SAT/SMT), mechanical theorem proving, model checking, or program analysis
- Demonstrated science depth in a specific research area, evidenced through publications, thesis work, or equivalent contributions
Preferred Qualifications
- Experience implementing algorithms using formal methods toolkits (e.g. Lean, Dafny, Isabelle, Rocq, Z3, SAT/SMT solvers, or domain-specific verification frameworks)
- Experience applying formal methods or automated reasoning to real-world software, security, or systems problems
- Experience programming in OCaml, Haskell, Rust, Scala, or a related functional or systems language
- Experience with AI-assisted development tools to accelerate research, coding, or evaluation
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The starting pay for this position is listed below. Starting Day 1 of employment, Amazon offers EAP, Mental Health Support, Medical Advice Line, 401(k) matching. Learn more about our benefits at https://hiring.amazon.com/why-amazon/benefits.
Seattle, WA, USA - 135,660.00 USD Annually
Eligibility requirements
Are enrolled in a PhD Can relocate to where the internship is based Work 40 hours/week minimum and commit to 12 week internship minimum Experience programming in Python, and where applicable, C++, Haskell, or Lean Experience in one or more of the following: mathematical logic, formal verification, satisfiability solving (SAT/SMT), mechanical theorem proving, model checking, or program analysis Demonstrated science depth in a specific research area, evidenced through publications, thesis work, or equivalent contributions
Tips for this phd opportunity
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