2027 Applied Science Internship - Automated Reasoning - United States, PhD Student Science Recruiting, Automated Reasoning

Amazon is hiring a 2027 Applied Science Internship - Automated Reasoning - United States, PhD Student Science Recruiting, Automated Reasoning in Seattle, United States. It pays $136k a year and Level rates it ; you can apply on Amazon.

Level's read on this job

On Level's scale, this HR role is Builds AI ●●●●: the job is building AI systems.
Pay on this posting starts 11% higher than the typical HR posting on Level.
The posting mentions Python, AWS and AI safety among its tools and skills.
Level classes it as an internship.
Amazon has 20,000+ other open roles on Level.

AI in this role

PhD intern developing automated reasoning and machine learning techniques for cloud infrastructure verification and AI safety.

PythonAWS

ai-safetyautomated-reasoningformal-methodstheorem-provingmachine-learninggenerative-ai

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

How we rate this

2027 Applied Science Internship - Automated Reasoning - United States, PhD Student Science Recruiting, Automated Reasoning at Amazon rates 85 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

●●●● Builds AI80 to 100
●●●○ Works on AI60 to 79
●●○○ Uses AI40 to 59
●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Key facts

2027 Applied Science Internship - Automated Reasoning - United States, PhD Student Science Recruiting, Automated Reasoning is an open job at Amazon.
Level rates this role AI Level 4 of 4: Builds AI.
The listed salary is $136k a year.
The role is based in US, WA, Seattle.
The job was posted on September 17, 2026.
Seniority: intern.
Applications are handled by Amazon. Apply on Amazon

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

AI SafetyAutomated ReasoningFormal MethodsTheorem ProvingMachine learningGenerative AIPythonAWS

Also common in HR jobs at this level

Java Computer vision Deep learning NLP Reinforcement learning PyTorch

Pay

This job starts at: $136k
Typical HR job: $122k

This posting starts 11% above the typical HR job. See HR jobs

Questions you could be asked

How do you think about the risk of an AI system in this kind of role failing silently?
Tell me about a project where automated reasoning was part of your work. What did you do?
Tell me about a project where formal methods was part of your work. What did you do?
Tell me about a project where theorem proving was part of your work. What did you do?
Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

List these exact terms on your resume: AI Safety, Automated Reasoning, Formal Methods, Theorem Proving, and Machine learning. An applicant tracking system matches the wording, not the idea.
Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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