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2023 Fall Applied Science Internship - Automated Reasoning and Storage Systems - United States, Student Science Recruiting
Amazon.comUnited Statesfull_timeVerifiedPosted 31 Mar 2023
💰 $204,620/yr($110,680/yr – $204,620/yr)
About the role
To ensure a great internship experience, please keep these things in mind. This is a full time internship and requires an individual to work 40 hours a week for the duration of the internship. Amazon requires an intern to be located where their assigned team is. Amazon is happy to provide relocation and housing assistance if you are located 50 miles or further from the office location.
We are looking for Masters or PhD students excited about working on Automated Reasoning or Storage System problems at the intersection of theory and practice to drive innovation and provide value for our customers.
AWS Automated Reasoning teams deliver tools that are called billions of times daily. Amazon development teams are integrating automated-reasoning tools such as Dafny, P, and SAW into their development processes, raising the bar on the security, durability, availability, and quality of our products. AWS Automated Reasoning teams are changing how computer systems built on top of the cloud are developed and operated.
AWS Automated Reasoning teams work in areas including: Distributed proof search, SAT and SMT solvers, Reasoning about distributed systems, Automating regulatory compliance, Program analysis and synthesis, Security and privacy, Cryptography, Static analysis, Property-based testing, Model-checking, Deductive verification, compilation into mainstream programming languages, Automatic test generation, and Static and dynamic methods for concurrent systems.
AWS Storage Systems teams manage trillions of objects in storage, retrieving them with predictable low latency, building software that deploys to thousands of hosts, achieving 99.999999999% (you didn’t read that wrong, that’s 11 nines!) durability. AWS storage services grapple with exciting problems at enormous scale. Amazon S3 powers businesses across the globe that make the lives of customers better every day, and forms the backbone for applications at all scales and in all industries ranging from multimedia to genomics. This scale and data diversity requires constant innovation in algorithms, systems and modeling.
AWS Storage Systems teams work in areas including: Error-correcting coding and durability modeling, system and distributed system performance optimization and modeling, designing and implementing distributed, multi-tenant systems, formal verification and strong, practical assurances of correctness, bits-IOPS-Watts: the interplay between computation, performance, and energy, data compression - both general-purpose and domain specific, research challenges with storage media, both existing and emerging, and exploring the intersection between storage and quantum technologies.
As an Applied Science Intern, you will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment who is comfortable with ambiguity.
Amazon believes that scientific innovation is essential to being the world’s most customer-centric company. Our ability to have impact at scale allows us to attract some of the brightest minds in Automated Reasoning and related fields. Our scientists work backwards to produce innovative solutions that delight our customers. Please visit https://www.amazon.science (https://www.amazon.science/) for more information.
· Enrolled in a Master’s degree program or equivalent in computer science or related fields.
· Experience with at least one of the following: formal specification, formal semantics, propositional logic (and SAT solving), first-order logic (and SMT solving), higher-order logics, temporal logics.
· Experience in understanding and ability to implement algorithms using both toolkits and self-developed code.
· Experience with Java, Rust, O'Caml, C/C++, or other programming language, as well as with Python or similar scripting language.
· Familiar with the core undergraduate curriculum of computer science.
· Experience with at least one of the following: Deductive verification (Dafny, Boogie, OpenJML, Frama-C, VCC), Interactive theorem proving (Coq, HOL-light, Isabelle), Model checking (I) of protocols (ii) of code. Explicit-state vs symbolic model checking, Symbolic/concolic test generation, Model-based testing, Checking conformance/refinement, Functional programming, types, monads, Invariant-based verification, Synthesis, Runtime verification/monitoring, Solver-aided languages, Static analysis.
· Technical fluency, comfort understanding and discussing logical con
We are looking for Masters or PhD students excited about working on Automated Reasoning or Storage System problems at the intersection of theory and practice to drive innovation and provide value for our customers.
AWS Automated Reasoning teams deliver tools that are called billions of times daily. Amazon development teams are integrating automated-reasoning tools such as Dafny, P, and SAW into their development processes, raising the bar on the security, durability, availability, and quality of our products. AWS Automated Reasoning teams are changing how computer systems built on top of the cloud are developed and operated.
AWS Automated Reasoning teams work in areas including: Distributed proof search, SAT and SMT solvers, Reasoning about distributed systems, Automating regulatory compliance, Program analysis and synthesis, Security and privacy, Cryptography, Static analysis, Property-based testing, Model-checking, Deductive verification, compilation into mainstream programming languages, Automatic test generation, and Static and dynamic methods for concurrent systems.
AWS Storage Systems teams manage trillions of objects in storage, retrieving them with predictable low latency, building software that deploys to thousands of hosts, achieving 99.999999999% (you didn’t read that wrong, that’s 11 nines!) durability. AWS storage services grapple with exciting problems at enormous scale. Amazon S3 powers businesses across the globe that make the lives of customers better every day, and forms the backbone for applications at all scales and in all industries ranging from multimedia to genomics. This scale and data diversity requires constant innovation in algorithms, systems and modeling.
AWS Storage Systems teams work in areas including: Error-correcting coding and durability modeling, system and distributed system performance optimization and modeling, designing and implementing distributed, multi-tenant systems, formal verification and strong, practical assurances of correctness, bits-IOPS-Watts: the interplay between computation, performance, and energy, data compression - both general-purpose and domain specific, research challenges with storage media, both existing and emerging, and exploring the intersection between storage and quantum technologies.
As an Applied Science Intern, you will work closely with Amazon scientists and other science interns to develop solutions and deploy them into production. The ideal scientist must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems. A successful candidate will be a self-starter with strong attention to detail and the ability to thrive in a fast-paced, ever-changing environment who is comfortable with ambiguity.
Amazon believes that scientific innovation is essential to being the world’s most customer-centric company. Our ability to have impact at scale allows us to attract some of the brightest minds in Automated Reasoning and related fields. Our scientists work backwards to produce innovative solutions that delight our customers. Please visit https://www.amazon.science (https://www.amazon.science/) for more information.
Basic Qualifications
· Enrolled in a Master’s degree program or equivalent in computer science or related fields.
· Experience with at least one of the following: formal specification, formal semantics, propositional logic (and SAT solving), first-order logic (and SMT solving), higher-order logics, temporal logics.
· Experience in understanding and ability to implement algorithms using both toolkits and self-developed code.
· Experience with Java, Rust, O'Caml, C/C++, or other programming language, as well as with Python or similar scripting language.
Preferred Qualifications
· Enrolled in a Ph.D. degree program in computer science or a related field.· Familiar with the core undergraduate curriculum of computer science.
· Experience with at least one of the following: Deductive verification (Dafny, Boogie, OpenJML, Frama-C, VCC), Interactive theorem proving (Coq, HOL-light, Isabelle), Model checking (I) of protocols (ii) of code. Explicit-state vs symbolic model checking, Symbolic/concolic test generation, Model-based testing, Checking conformance/refinement, Functional programming, types, monads, Invariant-based verification, Synthesis, Runtime verification/monitoring, Solver-aided languages, Static analysis.
· Technical fluency, comfort understanding and discussing logical con
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