AI Benchmarking Lead, Performance Benchmarking Evaluation
Job ID: | ADCI HYD 13 SEZ - H84
Join our mission-critical team supporting Seller Assistant, Amazon's Gen-AI powered copilot that helps sellers navigate Amazon's complex ecosystem and grow their businesses. As a Quality Assurance Specialist, you'll play a pivotal role in ensuring the reliability and accuracy of AI model evaluations as we scale from 61% to 90%+ active seller coverage worldwide.
About Seller Assistant
Seller Assistant is a conversational AI copilot that understands the full context of a seller's business. It intelligently orchestrates backend tools to deliver actionable, drilled-down responses and can independently complete complex tasks on behalf of sellers with their permission.
Our Scale and Impact
- Expanded to 2.44MM sellers (45x growth vs. Dec 2024)
- Currently serving 61% of active sellers worldwide across 9 international stores (CN2XX, IN, UK, DE, JP, BR, MX, AE, SA)
- Supporting four languages: English, Chinese, German, and Japanese
- 2026 Goal: Scale to 90%+ active sellers WW with 5 new store launches (France, Italy, Spain, Canada, Australia)
As a Quality Assurance Specialist/AI Benchmarking Lead, you will benchmark Seller Assistant AI models for relevancy, correctness, and completeness. The role focuses on evaluating audits, improving reliability, and ensuring quality standards.
Your primary responsibilities include:
- Evaluate audits performed by the core auditing team to increase confidence in evaluation metrics.
- Improve audit reliability and consistency through systematic measurement of auditor accuracy.
- Conduct targeted calibration to ensure quality standards across the auditing function.
- Enforce quality standards by quality-checking audits and providing actionable feedback to team members.
- Drive continuous improvement in audit processes and methodologies.
Key Responsibilities
- Conduct quality checks on audits performed by the core auditing team.
- Identify rubric gaps and evaluation ambiguities that lead to inconsistent audit outcomes.
- Surface high-confidence product issues earlier by validating and categorizing model failures.
- Serve as point of contact for annotation tasks across ML data process areas, ensuring quality execution and delivery.
- Understand dependencies across ML data workflows and articulate customer impact effectively.
- Modify existing annotation methods and update SOPs.
- Document SOP changes, secure approval, share knowledge with the team, and audit adoption and execution.
- Test new SOPs and tools, providing feedback on quality and improvement recommendations to support onboarding.
- Structure data collection, analyze results and share inputs for SOP changes.
- Collate, track, and report progress on key metrics agreed to with respective stakeholders (e.g., Program managers, Applied Scientist) specific to your functional area.
- Identify operational issues related to process and tooling and recommend suggestions to improve key project metrics such as productivity and quality.
Basic Qualifications
- Bachelor's degree or equivalent.
- Experience in natural language data labeling, data annotation, linguistic annotation or other forms of data markup.
- Technical Skills: Proficiency in MS Excel; basic understanding of SQL and Python.
- Experience with Microsoft Office products and applications.
- Strong verbal and written communication skills in English.
- Knowledge about SOA and processes that deal with sellers.
Preferred Qualifications
- 1 to 3 years of equivalent experience.
- Performed annotation related tasks across ML data process areas.
- Strong knowledge of process documentation, analysis knowledge.
- Technical proficiency in SQL querying and Python programming for data analysis.
- Strong analytical and problem-solving skills.
- Ability to work independently and as part of a team.
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Posted: April 24, 2026 (Updated 17 days ago)
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
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