Amazon Machine Learning Engineer Workforce Solutions - Analytics Tech 

United States, Washington, Bellevue 

900716917

The types of initiatives you can expect to work but not limited to include:
- Developing personalized recommendation systems.Key job responsibilities- Develop ML/LLM workflows and end-to-end pipelines for data preparation, training, deployment, monitoring, etc., and ensure a high bar for the quality of architecture and design of our AI ML systems and data infrastructure
- Leverage AWS AI services and other internal / publicly available external tools & services to accelerate our AI investments
- Detail-oriented, always backs up ideas with facts. Understands complex application data flows and bridge the gap between technical and business app requirement
- Identify state of the art models / solutions to enable new capabilities for code migration and code testing, drive down tech debt and increase operational efficiency
- Share expert knowledge in performance, large scale distributed system scalability, system architecture, and engineering best practices
- Provide thought leadership and hands-on support in selecting, defining, training and fine-tuning Large Language Models (LLMs), prompt engineering, and other GenAI efforts.- Define data and feature validation strategies
- Deploy models to production systems and operate them including monitoring and troubleshooting
A day in the life
As a Machine Learning Engineer, you will work closely with science teams to bring research to production. This is a role that combines engineering knowledge, technical strength, and product focus. It will be your job to implement novel ML systems, product integrations, and performance optimizations. You will guide the direction of a MLOPS automation framework via collaboration with the engineering and research communities.
You will collaborate with software engineering teams to integrate successful experimental results into complex Amazon production systems and you will provide support for business continuity on a rotating on call.

- 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

- 3+ years of full software development life cycle, including coding standards, code reviews, source control management, build processes, testing, and operations experience
- Bachelor's degree in computer science or equivalent