Senior ML Engineer, Generative BI & LLMs — Flexible Hours

Amazon.com Services LLC

Seattle (WA)

On-site

USD 120,000 - 190,000

Full time

14 days+
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Job summary

Amazon.com Services LLC in Seattle, WA is seeking a Machine Learning Engineer (MLE II) for the QuickSight team. You will design and deploy ML models that power the NLQ capabilities, enabling business users to ask questions and receive instant insights.

Work on prototypes, experiments, and production deployments, with a focus on LLMs, NLP, and scalable systems. This role offers mentorship, growth opportunities, and a chance to influence the next generation of Generative BI.

Qualifications

  • 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.

Responsibilities

  • Understand business objectives, product requirements and develop ML algorithms that achieve them.
  • Build Prototypes, POC to determine feasibility.
  • Run experiments to assess performance and improvements.
  • Provide ideas and alternatives to drive a product/feature.
  • Define data and feature validation strategies
  • Deploy models to production systems and operate them including monitoring and troubleshooting.

Skills

Software development
Machine Learning
NLP / Data Mining

Job description

Amazon.com Services LLC in Seattle, WA is seeking a Machine Learning Engineer (MLE II) for the QuickSight team. You will design and deploy ML models that power the NLQ capabilities, enabling business users to ask questions and receive instant insights.

Work on prototypes, experiments, and production deployments, with a focus on LLMs, NLP, and scalable systems. This role offers mentorship, growth opportunities, and a chance to influence the next generation of Generative BI.

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