Applied Scientist, AWS Automated Reasoning in London

Applied Scientist, AWS Automated Reasoning in London

London Full-Time 60000 - 80000 £ / year (est.) Home office (partial)
Amazon Science

At a Glance

  • Tasks: Join us to develop cutting-edge software verification tools using AI and cloud technology.
  • Company: Be part of AWS, a leader in innovative cloud solutions.
  • Benefits: Enjoy competitive pay, flexible work options, and opportunities for professional growth.
  • Other info: Collaborative team focused on pioneering AI-based verification methods.
  • Why this job: Make a real impact on security and reliability for millions of developers worldwide.
  • Qualifications: PhD or Master's in CS, CE, ML; programming skills in Java, C++, or Python.

The predicted salary is between 60000 - 80000 £ per year.

The Agentic Automated Reasoning Group is building the next generation of software verification tools combining advances in artificial intelligence, the computational capacity of the cloud, and our deep expertise in the domain. Join us if you want to be a part of this transformational endeavour.

The Strata team is seeking an applied scientist with broad interest and expertise in model checking, interactive theorem proving, programming language semantics, and generative AI. You will combine your expertise with that of your coworkers to build new tools that solve code analysis problems previously considered beyond reach. Our application areas span all the way from Infrastructure as Code to high‑performance cryptography written in assembly code, while our methods span from interactive theorem proving to automated test generation.

Each day, hundreds of thousands of developers make billions of transactions worldwide on AWS. They harness the power of the cloud to enable innovative applications, websites, and businesses. Using automated reasoning technology and mathematical proofs, AWS allows customers to answer questions about security, availability, durability and functional correctness. We call this provable security, absolute assurance in security of the cloud and in the cloud.

Key Job Responsibilities
  • Work with customer teams to understand the nature of their software and the properties they need to establish of it.
  • Identify tools and methods capable of addressing the verification needs of customers, including any novel analysis capabilities required.
  • Use techniques spanning property‑based testing to model checkers, and interactive theorem provers to establish program properties.
  • Explore generative AI techniques to help customers formalize their requirements, find revealing tests, generate required boiler plate for testing and model checking, and find and repair program proofs.

About The Team: The Agentic Automated Reasoning Group at AWS develops and applies state‑of‑the‑art formal methods and automated reasoning techniques to ensure the security, reliability and correctness of AWS services and customer applications, with a strong focus on AI‑based agents. Our work innovates tools and services to perform verification at scale and apply them to build safe and secure systems at AWS. We are also pioneering the use of formal verification and automated reasoning to develop agentic systems, ensuring AI agents operate within defined safety boundaries.

Basic Qualifications
  • PhD, or a Master's degree and experience in CS, CE, ML or related field.
  • Experience in patents or publications at top‑tier peer‑reviewed conferences or journals.
  • Experience programming in Java, C++, Python or related language.
  • Experience in any of the following areas: algorithms and data structures, parsing, numerical optimisation, data mining, parallel and distributed computing, high‑performance computing.
  • Experience in building machine learning models for business application.
Preferred Qualifications
  • Experience using Unix/Linux.
  • Experience in professional software development.

Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.

Applied Scientist, AWS Automated Reasoning in London employer: Amazon Science

At AWS, we pride ourselves on fostering a culture of innovation and collaboration, where applied scientists can thrive in a dynamic environment that encourages continuous learning and professional growth. Our commitment to diversity and inclusion ensures that every voice is heard, while our cutting-edge projects in automated reasoning and AI provide unique opportunities to work on transformative technologies that impact millions globally. Join us in Seattle, where the vibrant tech community and access to world-class resources make it an ideal location for advancing your career in software verification.

Amazon Science

Contact Details:

Amazon Science Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Applied Scientist, AWS Automated Reasoning in London

Get Involved in Data Science Meetups

Tap into local data science meetups or workshops to connect with fellow enthusiasts and professionals. These events are goldmines for networking, and sometimes even lead directly to job openings at companies like Amazon Science!

Show Off Your Projects

Start building a public portfolio showcasing your data science projects on platforms like GitHub or personal websites. Highlight unique analyses or models you've developed. This not only demonstrates your skills but also gets your name out there for roles like Applied Scientist, AWS Automated Reasoning at Amazon Science.

Leverage Professional Networks

Join professional bodies related to data science, like the Data Science Society or similar organisations. Getting involved can lead to mentorship opportunities and insider knowledge about full-time positions at companies like Amazon Science.

Apply Directly through Our Website

When you find a suitable opening like Applied Scientist, AWS Automated Reasoning at Amazon Science, make sure to apply directly through our website. It gives you an edge and shows you're keen to join our team. Plus, who doesn’t love a direct application? It’s easier than navigating through job boards!

We think you need these skills to ace Applied Scientist, AWS Automated Reasoning in London

Model Checking
Interactive Theorem Proving
Programming Language Semantics
Generative AI
Property-Based Testing
Automated Test Generation
Java

Some tips for your application 🫡

Show Off Your Projects:In the world of data science, your projects can speak volumes about your skills. Make sure to showcase a few key projects in your CV or portfolio, especially those that highlight your ability to work with data sets, build models, or use relevant tools like Python, R, or SQL. Don’t forget to include links to any GitHub repositories if applicable!

Quantify Your Achievements:Employers love numbers! When drafting your CV, highlight your achievements with quantifiable results. For instance, mention how your data analysis led to a certain percentage increase in efficiency or revenue at a previous job or project. These details can really make your application pop!

Craft a Tailored Cover Letter:For a full-time role at Amazon Science, your cover letter should reflect your passion for data science and your excitement about the specific projects or values of the company. Dive into why you’re a good fit, how your skills align with their needs, and any unique perspectives you can bring to the team.

Stand Out with Relevant Courses and Certifications:Although experience talks, relevant courses or certifications can be your ticket to impressing hiring managers at Amazon Science. Mention any standout courses you've completed that equipped you with essential skills, such as machine learning certifications or data visualisation courses. This shows your commitment to continuously developing your skills in the field!

How to prepare for a job interview at Amazon Science

Brush Up on Your Statistics

For a data science role, we need to seriously sharpen our statistics skills. Get ready to tackle technical questions on probability distributions, hypothesis testing, and regression analysis. These are often the bread and butter of data science interviews, so don't just skim over them!

Showcase Your Projects

Prepare a killer portfolio showcasing your data science projects. We should include details about the datasets used, the tools and techniques applied, and the impact of your findings. If we can walk them through a particularly challenging project or a cool visualisation that had real-world implications, it’ll really make us stand out!

Get Comfortable with Python and R

Most data science positions require us to be proficient in programming languages like Python and R. We should practice common libraries like pandas, NumPy, and scikit-learn, and be ready for live coding exercises or algorithm questions. Showing off our coding chops can really impress the interviewers at Amazon Science!

Prepare for Case Studies

Expect to encounter real-world case studies during the interview. We might be asked how we’d approach a data problem or analyse a dataset to extract insights. It's essential to think out loud and demonstrate our problem-solving process so that the interviewer can see our logical thinking in action.