Machine Learning Engineer

· Build and Innovate on industry defining Core Machine Learning infrastructure.
· Collaborate and Learn with world class scientists and engineers to grow skills in the space of real-world Machine Learning.
· Drive Ownership and be the face of critical and highly visible components and ideas in this constantly growing space.
· Spend dedicated time to learn by reading scientific papers / blogs and presenting to your team!

A day in the life
As a Machine Learning engineer on the Smart Home Machine Learning Core Infrastructure team, you will combine engineering best practices with your knowledge/learnings about Machine Learning to build cutting-edge infrastructure components and platforms that are highly scalable, extensible and robust to enable exponential growth and adoption of Machine Learning applications within the Organization. You will work very closely with Scientists and Engineers to help innovate and define the vision of products and features you own.

About the hiring group
The Smart Home Machine Core Infrastructure team aims to build cutting-edge infrastructure components and platforms that are highly scalable, extensible and robust to enable exponential growth and adoption of Machine Learning applications within the Organization. The customers include other customers of Alexa and Scientists and Engineers. The team thrives on an inclusive culture of diverse ideas and works on spending dedicated time to facilitate learning and exchange of ideas.

Job responsibilities
The Smart Home Machine Learning team is focused on making Alexa the user interface for the home. From the simplest voice commands (turn on the lights, turn down the heat) to use cases spanning home security, home entertainment, and the home environment, we are evolving Alexa into an intelligent, indispensable companion that automates daily routines, simplifies interaction with appliances and electronics, and helps customers get the most out of the technology in their lives.

As a Machine Learning SDE on the core infrastructure team you will develop design patterns, APIs, and high-scale services and platforms for machine learning that make the Smart Home intelligent. Your work will span Alexa skills, voice user interfaces, cloud services, and a rapidly-growing ecosystem of IoT devices and cutting-edge Machine Learning technology. You will have the satisfaction of working on a product your friends and family can relate to, and want to use every day. Like the world of smart phones less than 10 years ago, this is a rare opportunity to have a giant impact on the way people live.



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.

Basic Qualifications

· Master's Degree in Computer Science, Computer Engineering, Electrical Engineering, Mathematics
· Experience in system design, object programming, test driven development
· Experience with backend services in the cloud.
· Experience with the tools of the trade, including a variety of modern programming languages (Java, Ruby, Javascript, C/C++, Objective C, Python) and open-source technologies (Linux, Spring, JQuery, PyFlask etc)

Preferred Qualifications

· Experience designing internet-scale public APIs.
· Experience building solutions for home networks, IoT device and cloud systems, context-awareness, pervasive computing, or home/industrial control systems.
· Experience working with modern tools for big data processing and scalable machine learning (e.g., AWS, Kafka, Kinesis, Apache Spark, Hadoop, SQL, NoSQL).
· Experience with building and operating customer facing, cloud-based, production software systems.
· Demonstrated leadership abilities in an engineering environment in driving operational excellence and best practices.
· Ability to effectively articulate technical challenges and solutions and deal well with ambiguous/undefined problems; ability to think abstractly.
· Excellence in written and verbal technical communication for both technical and non-tech audiences.