Amazon Machine Learning Engineer Amazon 

United States, Washington, Seattle 

201499283

Key job responsibilities
As an Machine Learning Engineer on this team, you will
-Lead end-to-end Machine Learning projects that have a high degree of ambiguity, scale, complexity.
-Focus on Model Deployment, including all tasks necessary to turn a prototype into a production model, such as 1) model data pipelines: building data pipelines to produce inputs for training and inference in both online and offline contexts. 2) Training and inference pipelines: orchestration of model training and inference jobs. 3) Post-inference work: work required after the model’s output to serve business needs such as integration with engineering systems.
-Establish scalable, efficient, automated processes for large-scale data analysis, machine-learning model development, model validation and serving.
-Contribute to our ML Infrastructure, such as enhancements to our live model and experimentation platform.
-Maintenance and Operational Excellence: Regular maintenance and monitoring expected of any complex system/service.
-Contribute to building an infrastructure that facilitates end-to-end ML workflows.

- 3+ years of non-internship professional software development experience
- 2+ years of non-internship design or architecture (design patterns, reliability and scaling) of new and existing systems experience
- Experience programming with at least one software programming language
- Experience in machine learning, data mining, information retrieval, statistics or natural language processing
- Experienced in large scale AI and ML infrastructure, AWS ML tools such as SageMaker

- 3+ 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 running A/B tests in production and knowledge of causal inference and other modern machine learning techniques