Amazon is seeking an experienced and senior Applied Scientist to join MIND (Machine Intelligence for Networks and Devices) team within OpsTech Infrastructure Engineering (OTIE) organization to transform our network operations. The vision for OTIE is to be the invisible scaffolding to provide Amazon’s network and device infrastructure for Global Operations. OTIE delivers 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 science team, you will apply your deep modeling and statistical knowledge to concrete business 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.
A day in the life
Amazon offers a full range of benefits that support you and eligible family members, including domestic partners and their children. Benefits can vary by location, the number of regularly scheduled hours you work, length of employment, and job status such as seasonal or temporary employment.
The benefits that generally apply to regular, full-time employees include:
- Medical, Dental, and Vision Coverage
- Maternity and Parental Leave Options
- Paid Time Off (PTO)
- 401(k) Plan
If you are not sure that every qualification on the list above describes you exactly, we'd still love to hear from you!
At Amazon, we value people with unique backgrounds, experiences, and skillsets. If you’re passionate about this role and want to make an impact on a global scale, please apply!
About the team
Our Vision is to enable OTIE to provide the world’s most reliable and available network for WW Ops through self-aware, intent-driven, and autonomous AI/ML systems that deliver resilience at scale.
Our Mission is to develop simple, scalable, and ethical AI/ML solutions that transform complex operational data into actionable intelligence for network engineering and device technologies. We leverage existing tools and expertise, where available, to solve customer problems while continuously pushing the boundaries of what AI can achieve, ultimately enhancing network reliability, optimizing device performance, and empowering data-driven decision making across the organization.- PhD, or Master's degree and 6+ years of applied research experience
- 5+ years of building machine learning models for business application experience
- Experience programming in Java, C++, Python or related language
- Experience with neural deep learning methods and machine learning- 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 an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit
https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
