As a Machine Learning Engineer you will collaborate with scientists on developing and evaluating machine learning models using large datasets such as audio features, meta-data, search queries or customer’s listening behavior to improve the customer experience through better recommendations, search results, or song sequencing.
You will own scaling up successful prototypes and implementing a reliable automated production workflow for the model. You will collaborate with software development engineers to integrate the model with the customer experience.
Imagine being a part of an agile team where your ideas have the potential to reach millions. Picture working on cutting-edge consumer-facing products, where every single team member is a critical voice in the decision-making process. Envision being able to leverage the resources of a Fortune-500 company within the atmosphere of a start-up.
Welcome to Amazon Music, where ideas are born, and come to life as Amazon Music Unlimited, Prime Music, and the digital music store. Amazon Music offerings are available in multiple countries, and our applications support our mission of delivering music to customers in a way that enhances their day-to-day lives.
We can be found on platforms such as the Amazon Echo, Kindle Fire, iOS, and Android as well as on a mixture of home and auto streaming platforms
· Bachelor’s degree in Computer Science, Computer Engineering or related technical discipline
· 3+ years of relevant engineering experience
· Experience with back-end distributed systems
· Knowledge of the Agile Development Methodology
· 5+ years of relevant engineering experience
· Deep hands-on technical expertise in service oriented architecture, preferably in live-streaming technologies
· Strong business and technical vision
· Ability to handle multiple contending priorities in an energizing environment
· A deep understanding of software development in a team, and experience shipping software on time
· Extraordinary customer relationship skills including the ability to discover the true requirements underlying feature requests, recommend alternative technical and business approaches, and lead engineering efforts with optimal solutions
Job ID: 656738