Software Development Engineer Internship - CloudTune team

Job Description

The CloudTune - FRAM team is building cutting edge scaling solutions for Amazon internal Service Oriented Architecture. We are creating a world-class scaling systems and tools and we want you to be part of it.

CloudTune aims to improve forecasts accuracy and accelerate the dynamics of hardware infrastructure scaling and descaling in order to reach peak optimum hardware scaling levels over a minimum time window followed by rapid descaling. CloudTune will be able to dynamically scale fleets and is robust against changes of service behavior induced by innovation, business logic changes and downstream dependencies. Our goal is efficient host utilization that will reduce the large engineering effort spent by teams every year to prepare for large scale events. FRAM Team is in charge of Scaling Planner, a system that uses a hybrid approach, both reactive and predictive scaling based on host level metrics and forecast traffic volume, to predict and take just in time hardware scaling decisions. In addition to Scaling Planner we also develop and maintain Downshift, a tool for service owners to load test their service using production traffic by shifting more traffic to particular hosts in their fleet.

As a CloudTune FRAM intern you will be working along side our software engineers and applied scientists on challenging problems with the potential for making big impact.

We are looking forward to receiving your application by 30th of March 2018.

Basic Qualifications

• Fundamentals in data structures, and algorithm design;
• Knowledge of web technologies;
• Basic understanding of software architecture and design issues;
• Ability to effectively articulate technical challenges and solutions;
• Adept at handling ambiguous or undefined challenges through abstract thinking;
• Currently enrolled in an accredited college or university, actively pursuing a technical degree.

Preferred Qualifications

• Demonstrated coding skills : C/C++ and/or Java, preferably on a Linux platform.