ML Data Associate III, AWS Quick
Amazon · Posted Oct 14
E-commerce, cloud computing, online advertising, and digital streaming services
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About the role
Amazon Web Services (AWS) is the world's most comprehensive and broadly adopted cloud platform, and this role sits within the AWS Quick team, validating the natural language features of its product. The work spans linguistic testing, model output evaluation, and annotation quality for AI/ML and large language model systems. The ML Data Associate III will design linguistic test cases, build evaluation guidelines and rubrics, analyze results with Python and SQL, and partner with engineers, scientists, and PMs to triage language-related defects ahead of releases.
What you will do
- 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
Skills used in this role
What the employer is looking for
- 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
- Experience programming in Python or a related language
- Proficient in SQL
Benefits and support
- Compensation and benefits are detailed in the job posting
About Amazon
Amazon.com, Inc. is a multinational technology conglomerate focusing on e-commerce, cloud computing, online advertising, digital streaming, and artificial intelligence. Recognized as one of the world's most valuable brands, it operates the largest internet retail marketplace globally alongside its prominent cloud platform, Amazon Web Services (AWS).
- Industry
- E-Commerce
- Company size
- 1576000+ employees
- Founded
- 1994-07-05
- Location
- Seattle, Washington, USA
- Funding stage
- Public Company
Funding
Public Company · $8M raised
- 2013-03-22Post Ipo Debt$200M
Leadership
President and Chief Executive Officer
Founder and Executive Chair
Senior Vice President and Chief Financial Officer
Matt Garman
CEO, Amazon Web Services
CEO, Worldwide Amazon Stores
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