You will safeguard the quality of our AI and GenAI features by evaluating model outputs, creating golden datasets, and guiding continuous improvements in collaboration with data scientists and engineers. Be the guide to the team as the team creates a robust methodology and framework that will drive evaluation of hundreds of AI agents.

Responsibilities

Validate AI Output Review model results across text, documents, audio, and video; flag errors and improvement opportunities.
Create Golden Datasets Build and maintain high-quality reference data with help from subject-matter experts.
Data Annotation Accurately label multi-modal data and perform light preprocessing (e.g., text cleanup, image resizing).
Quality Analytics Run accuracy metrics, trend analyses, and clustering to gauge model performance. Fine-Tune Model Code Adjust training scripts and parameters to boost accuracy and keep behavior consistent across models.
Process Improvement & Documentation Refine annotation workflows and keep clear records of methods, findings, and best practices.
Cross-Functional Collaboration Partner with ML engineers, product managers, and QA peers to ship reliable, user-ready features.

Required Qualifications

2 to 4 years of experience in data science/AI/ML. Specific experience in evaluation of AI results is strongly preferred
Working knowledge of AI/ML evaluation techniques
Solid analytical skills and meticulous attention to detail.
Bachelor s or Master s in Computer Science, Data Science, or a related field.
Strong English written and verbal communication.
Self-directed, organized, and comfortable with ambiguous problem spaces.

#LI-SG1

Equal Opportunity Statement

Did you read the requirements as a checklist and not tick every box? Dont rule yourself out! If this role resonates with you, hit the apply button.

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