Description

Amazon is seeking an experienced Applied Scientist to join our OpsTech Infrastructure Engineering (OTIE) team. The vision for our organization is to be the invisible scaffolding to provide Amazon’s network and device infrastructure for Global Operations. We deliver flexible, low-touch, cost-efficient infrastructure products by leveraging data, analytics, and automation to build a highly scalable and accessible network. If you are passionate about working with big data and thrive in a collaborative, innovative environment, we want to hear from you.

As a member of the core team, you will apply your deep coding, modeling and statistical knowledge to concrete problems that have broad cross-organizational, global, and technology impact. Your work will within a cross-functional team of engineers, data scientists and data engineers to focus on retrieving, cleansing and preparing large scale datasets, training and evaluating models and deploying them to production where we continuously monitor and evaluate. You will work on large engineering efforts that solve significantly complex problems facing global customers. You will be trusted to operate with complete independence and are often assigned to focus on areas where the business and/or architectural strategy has not yet been defined. You must be equally comfortable digging in to business requirements as you are drilling into design with development teams and developing production ready learning models. You consistently bring strong, data-driven business and technical judgment to decisions.

You will work with internal and external stakeholders, cross-functional partners, and our customers. You are empowered to bring new technologies to your solutions. If you crave a sense of ownership, this is the place to be.

Key job responsibilities

• Research, design, implement and evaluate complex network engineering decision making algorithms integrating across multiple disciplines.

• Create experiments and prototype implementations of algorithms and optimization techniques.

• Work closely with software engineering team members to drive scalable, real-time implementations.

• Be willing to represent Amazon in academia community through publications and scientific presentations.

• Work with stakeholders across engineers, science, and operations teams to iterate on systems design and implementation.

Basic Qualifications

• 3+ years of building machine learning models for business application experience

• PhD, or Master's degree and 6+ years of applied research experience

• Knowledge of programming languages such as C/C++, Python, Java or Perl

• Experience programming in Java, C++, Python or related language

• Experience with neural deep learning methods and machine learning

Preferred Qualifications

• Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.

• Experience with large scale distributed systems such as Hadoop, Spark etc.

• • Familiarity with Network Engineering/ Network Management
• • Publications at top-tier peer-reviewed conferences or journals

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us.