Applied Scientist, S3-ARG

Key Skills

Ruby on Rails, Java Programming, Leadership, UX design, Python Programming, C++, C Programming, SQL, AWS, Amazon Simple Storage Service (S3), Mathematics, Data Analysis

Job Description

Amazon's Simple Storage Service (S3) offers industry-leading scalability, data availability, security, and performance. S3’s Automated Reasoning Group (S3-ARG) develops and applies automated reasoning techniques to deliver correct, secure, durable, and available distributed systems and storage services. S3 is complex: it consists of hundreds of micro-services each of which is a distributed system. With a very large number of servers and 10s of millions of requests per second, it is also highly concurrent. S3 has a sizable codebase, developed and maintained by a large team of engineers. Getting such a complex and fast-evolving system right requires developing cutting edge automated reasoning methods that are continuously integrated into the software development process. This is what our team does.

We are a diverse team and are looking for teammates who are enthusiastic to work on these problems and further the state of the art with us. We are seeking candidates who are deep in one area of expertise but also broad enough to take on the most complex cloud computing challenges. If you are interested in exploring, please e-mail

Key job responsibilities

• Researching, designing and developing innovative solutions to complex problems in storage systems such as S3
• Defining and executing on a research roadmap for S3. You’ll know and talk with your stakeholders on a regular basis, as well as using data and metrics to understand how your service is used, and build and deliver on a roadmap that delights our customers.
• Develop novel automated reasoning techniques and tools while working with the engineering team to integrate them into our projects
• Interact closely with the open-source, academic and research communities
• Work with other acclaimed engineers and world famous scientists

A day in the life

We work on techniques ranging from deductive proofs to model checking, from static analysis to runtime verification of protocols. We work both at the design and the code level, and connecting the two is essential for us. We partner with development teams to make sure that our methods are deployed across S3 and that correctness is maintained as the software evolves. We have had significant success with adoption and we are key contributors to recent S3 launches such as strong consistency. We are developing innovative methods all the time. We publish our results at conferences and journals.

About the team

Inclusive Team Culture

Here at AWS, we embrace our differences. We are committed to furthering our culture of inclusion. We have ten employee-led affinity groups, reaching 40,000 employees in over 190 chapters globally. We have innovative benefit offerings, and host annual and ongoing learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (gender diversity) conferences. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Work/Life Balance

Our team puts a high value on work-life balance. It isn’t about how many hours you spend at home or at work; it’s about the flow you establish that brings energy to both parts of your life. We believe striking the right balance between your personal and professional life is critical to life-long happiness and fulfillment. We offer flexibility in working hours and encourage you to find your own balance between your work and personal lives.

Mentorship & Career Growth

Our team is dedicated to supporting new members. We have a broad mix of experience levels and tenures, and we’re building an environment that celebrates knowledge sharing and mentorship. We care about your career growth and strive to assign projects based on what will help each team member develop into a better-rounded professional and enable them to take on more complex tasks in the future.

BASIC QUALIFICATIONS

• M.S. or Ph.D. degree in Electrical Engineering, Computer Science, Mathematics, or related technical field
• Proven industrial/academic experience in formal verification, program analysis, constraint-solving, and/or theorem proving
• Experience with programming languages such as Java, Scala, C/C++, Ruby, or Python and open-source technologies

PREFERRED QUALIFICATIONS

• Ph.D. degree in Electrical Engineering, Computer Science, Mathematics, or related technical field
• Software development experience of compilers, interpreters or related tools
• Demonstrated experience in transforming theoretical concepts into consumer products
• Record of publications at well-regarded conferences and in associated journals in automated reasoning or formal methods