Machine Learning Engineer, Workforce Solutions - Talent Mobility
Amazon.com
The Workforce Solutions Talent Mobility team is actively seeking candidates who are interested in solving challenging problems using latest developments in Large Language Models and Artificial Intelligence (AI). We are looking for a talented AI and Machine Learning (ML) engineer with a solid background in the design and development of scalable AI and ML systems and services, deep passion for building ML-powered products, a proven track record of executing complex projects, and delivering high business and customer impact. Your contributions will be instrumental to tackle staffing challenges within Amazon's warehouses.
Key job responsibilities
- Design, implement, and productionize AI/ML models by working very closely with scientists on the team.
- 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.
- Mentor other engineers, especially on AI/ML initiatives, and foster a culture of learning & collaboration.
. 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 member of our team, you'll work on projects that directly impact over a million Amazon associates. This role will provide exposure to state-of-the-art innovations in AI/ML systems (including GenAI). Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Anthropic’s Claude / Mistral, among others.
The types of initiatives you can expect to work but not limited to include:
- Developing personalized recommendation systems.
- Building AI Assistant tools that have cross-Amazon user adoption.
About the team
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.
Key job responsibilities
- Design, implement, and productionize AI/ML models by working very closely with scientists on the team.
- 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.
- Mentor other engineers, especially on AI/ML initiatives, and foster a culture of learning & collaboration.
. 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 member of our team, you'll work on projects that directly impact over a million Amazon associates. This role will provide exposure to state-of-the-art innovations in AI/ML systems (including GenAI). Technologies you will have exposure to, and/or will work with, include AWS Bedrock, Amazon Q, SageMaker, and Foundational Models such as Anthropic’s Claude / Mistral, among others.
The types of initiatives you can expect to work but not limited to include:
- Developing personalized recommendation systems.
- Building AI Assistant tools that have cross-Amazon user adoption.
About the team
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.
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