ML Data Associate III, AWS Quick

ML Data Associate III, AWS Quick

Design and execute linguistic test cases to validate Quick's natural language features across diverse inputs, edge cases, and user scenarios.
Evaluate model outputs for accuracy, fluency, and relevance by applying linguistic expertise to identify regressions, hallucinations, and quality gaps.
Develop and maintain testing guidelines and rubrics that ensure consistent, repeatable evaluation standards across annotators and test cycles.
Analyze test results and report findings using Python and SQL to surface patterns, quantify defect rates, and prioritize issues for engineering teams.
Collaborate with engineers, scientists, and PMs to define acceptance criteria, triage language-related bugs, and validate fixes before releases
Work on high complex annotations and audits as needed
Work effectively both independently and as part of a team
Uphold a high bar for quality while delivering accurate work at pace
Apply strong attention to detail and Critically assess data quality
Manage competing tasks and adapt quickly to shifting priorities
Take ownership and Exercise sound judgment in escalating
Handle highly complex tasks and Scale with growing workloads

About the team
Diverse Experiences
AWS values diverse experiences. Even if you do not meet all of the qualifications and skills listed in the job description, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.

About AWS
Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.

Inclusive Team Culture
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Work/Life Balance
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Mentorship & Career Growth
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Basic Qualifications

- 3+ years of working with Data & AI related technologies, including, but not limited to, AI/ML, GenAI, Analytics, Database, and/or Storage experience
- Experience with Machine Learning and Large Language Model fundamentals, including architecture, training/inference lifecycles, and optimization of model execution
- Completed a bachelor’s degree in engineering, Computer Science, Machine Learning, Operations Research, Data Science/ Linguistics
- Knowledge of linguistic fundamentals, including handling ambiguity, natural language processing concepts, and query (Q&A) interpretation

Preferred Qualifications

- Experience programming in Python or a related language
- Proficient in SQL

Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.

Experience Level

Mid Level