- 1+ years of experience contributing to the architecture and design (architecture, design patterns, reliability and scaling) of new and current systems.
- 2+ years of non-internship professional software development experience
- Programming experience with at least one modern language such as Java, C++, or C# including object-oriented design
Our mission is to build a system that proactively anticipates what customers need next, and informs the customer of it at the right moment and on the right channel. We continually innovate to recommend and optimize for the most relevant proactive experiences for our customers. As a Machine Learning Engineer for the Alexa Feedback team, you will be responsible for translating business and functional requirements into concrete deliverables with the design, development, testing, and deployment of highly scalable distributed services. You will also partner with scientists and other engineers to help invent, implement, and connect sophisticated algorithms to our cloud based engines. In this role, you will be exposed to machine learning problems spanning personalization, contextual bandits, recommender systems, and reinforcement learning while developing novel solutions using large-scale real-world datasets to help provide the best-possible experience for our customers. Your solutions will enable models to get to market faster, automate the evaluation and improvement of ML results, and enable Alexa to learn from past customer interactions to drive future engagement and utility.
Key job responsibilities
Designing, developing and maintaining core system features, services and engines
Helping define product features, drive the system architecture, and spearhead the best practices that enable a quality product
Working with scientists and other engineers to investigate design approaches, prototype new technology, and evaluate technical feasibility
Operating in an Agile/Scrum environment to deliver high quality software
- Master's Degree in Computer Science (Machine Learning, AI, Statistics, or equivalent)
- Experiences related to AWS services such as SageMaker, EMR, S3, DynamoDB and EC2
- Experience with programming languages such as Scala, Java or Python a plus
- Experience with Big Data technologies such as AWS, Hadoop, Spark
- Experience with common machine learning techniques such as preprocessing data, training and evaluation of classification and regression models, and statistical evaluation of experimental data.
- Experience building recommender/optimization systems and/or machine learning models in production using distributed computing and big data processing concepts and technologies.
- Knowledge of professional software engineering practices & best practices for the full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations
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.