Sr. Machine Learning Engineer, Music SLU

Are you excited about cutting-edge ML technologies in the areas of Natural Language Processing (NLP) and Conversational AI? If you'd like to work alongside a team of passionate and talented scientists and engineers on solving challenges around understanding various forms of music intent and breaking new ground in powering interactive voice experiences, then come and join Amazon Music Spoken Language Understanding (AMSLU) team. The AMSLU team seeks to hire an ML Engineer who has a solid background in design and development of scalable AI/ML systems, deep passion for building data-driven products, ability to communicate engineering insights, and has a proven track record of executing complex projects and delivering high business impact.

The AMSLU team sits at the core of reinventing the voice experience for Amazon Music. The team owns all Spoken Language Understanding aspects on Amazon Music and also enables new voice experiences through third-party assistants such as Google Assistant, Siri, etc. We also build state-of-the art foundational technologies for better understanding user intent and behavior and study its impact on engagement and voice experience. You will help us deliver customers the best music experience throughout their journey!

Key job responsibilities
As an ML Engineer you will design and develop ML solutions that involves large-scale distributed data processing. You will have responsibility to help define requirements, create software designs, implement code to these specifications, and support products while deployed and used by our customers. As an ML Engineer, you will be expected to:


• Work with Applied Scientists, Data Scientists, Research Scientists and ML Engineers to invent, design and deliver Machine Learning solutions in production at scale.
• Develop ML workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure the quality of architecture and design of our ML systems and data infrastructure.
• Develop data-driven feedback loops and real-time decision making frameworks to provide the best experience for our customers.

Prior domain knowledge in NLU is a plus, though not required. However, strong motivation to learn ML, AI and NLU is critical for candidate to be successful in the role.

A day in the life

• Design, develop and maintain core system features, services and engines.
• Help define product features, drive system architecture, and spearhead best practices that enable a quality product.
• Work with scientists and other engineers to investigate design approaches, prototype new solutions, and evaluate technical feasibility.
• Operate in an Agile/Scrum environment to deliver high quality software against aggressive schedules.

About the team
We believe that Amazon Music on Alexa provides the best voice-enabled music experience in the world. Its Day 1 in the world of voice-enabled devices and we're looking for great engineers to help us make it even better.

As a member of the Amazon Music SLU Team, you will be responsible for leading the effort to invent and improve the ways that customers can ask for what they want to hear in Amazon Music Unlimited, Prime Music or Ad-supported Free Tier. Our team works at the intersections of big data, music personalization, machine learning, and building highly-available run-time services.

We develop software in Java, Python, Spark, and use various AWS technologies.

Basic Qualifications

• 5+ years of non-internship professional software development experience
• 5+ years of programming with at least one software programming language experience
• 5+ years of leading design or architecture (design patterns, reliability and scaling) of new and existing systems experience
• Experience as a mentor, tech lead or leading an engineering team

Preferred Qualifications

• 5+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
• Master's degree in computer science or equivalent
• Experience with Apache Spark and Amazon AWS platform (SageMaker, Redshift, EMR, Glue, Step Functions, Lambda, Batch, etc.).
• Experience with machine learning and deep learning libraries/techniques in the area of NLU.
• 5+ years of experience building scalable machine-learning infrastructure and big data systems.

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.amaz