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2026 Fall Applied Science Internship - Automated Reasoning - United States, PhD Student Science Recruiting

Amazon

2026 Fall Applied Science Internship - Automated Reasoning - United States, PhD Student Science Recruiting

Amazon

Seattle, WA, USA

·

On-site

·

Internship

·

1w ago

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 cutting-edge 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.

As an Applied Science Intern, you'll have the opportunity to work alongside our brilliant scientists and contribute to groundbreaking projects. From distributed proof search and SAT/SMT solvers to program analysis, synthesis, and verification, you'll tackle complex challenges at the intersection of theory and practice, driving innovation and delivering tangible value to our customers.

This internship is not just about executing tasks – you'll explore novel approaches to solving intricate automated reasoning problems. You'll dive deep into cutting-edge research, leveraging your expertise to develop innovative solutions. You'll work on deploying your solutions into production, witnessing the real-world impact of your contributions.

Throughout your journey, you'll have access to unparalleled resources, including state-of-the-art computing infrastructure, cutting-edge research papers, and mentorship from industry luminaries. This immersive experience will not only sharpen your technical skills but also cultivate your ability to think critically, communicate effectively, and thrive in a fast-paced, innovative environment.

Join us and be part of a team that is shaping the future of cloud computing through the power of Automated Reasoning. Apply now and unlock your potential!

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

The ideal candidate should possess the ability to work collaboratively with diverse groups and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter, comfortable with ambiguity, with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment.

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

Basic Qualifications

  • Are enrolled in a PhD
  • Can relocate to where the internship is based
  • Experience programming or scripting language like Python, Java, C or C++
  • Work 40 hours/week minimum and commit to 12 week internship minimum
  • Experience with one or more of the following: Knowledge Graphs and Extraction, Neural Networks/GNNs, Data Structures and Algorithms, Time Series, Machine Learning, Natural Language Processing, Deep Learning, Large Language Models, Graph Modeling, Knowledge Graphs and Extraction, Programming/Scripting Languages

Preferred Qualifications

  • Have publications at top-tier peer-reviewed conferences or journals

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 base salary range for this position is listed below. Your Amazon package will include sign-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life & AD&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.

USA, WA, SEATTLE - 142,800.00 - 193,200.00 USD annually
USA, WA, Seattle - 142,800.00 - 193,200.00 USD annually

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About Amazon

Amazon

Amazon

Public

Amazon.com, Inc. is an American multinational technology company engaged in e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence.

10,001+

Employees

Seattle

Headquarters

$1.5T

Valuation

Reviews

2.9

10 reviews

Work-life balance

2.8

Compensation

3.7

Culture

2.5

Career

2.3

Management

2.1

35%

Recommend to a friend

Pros

Good pay and compensation

Strong benefits package

Flexible scheduling options

Cons

Poor management and leadership

Limited growth and promotion opportunities

High stress and demanding work environment

Salary Ranges

4 data points

L2

L3

L4

L5

L6

L2 · Data Analyst L2

0 reports

$108,330

total per year

Base

$43,332

Stock

$54,165

Bonus

$10,833

$75,831

$140,829

Interview experience

10 interviews

Difficulty

3.7

/ 5

Duration

21-35 weeks

Offer rate

20%

Experience

Positive 10%

Neutral 10%

Negative 80%

Interview process

1

Application Review

2

Recruiter Screen

3

Online Assessment

4

Technical Phone Screen

5

Onsite/Virtual Loop

6

Team Matching

7

Offer

Common questions

Coding/Algorithm

System Design

Behavioral/STAR

Leadership Principles

Technical Knowledge