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Senior Data Scientist for AI Model Evaluation and Data Collection

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Build datasets, evaluation rubrics, and reward signals to improve large language models. Design data slices to identify model failure modes across domains like finance, software, and enterprise workflows. Requires 1-4 years of experience in ML data collection and evaluation strategies.

Key Highlights
Design data slices to identify model failure modes in finance, software, and enterprise workflows
Develop evaluation rubrics and reward signals for RLHF and RLVR pipelines
1-4 years of experience in ML data collection and evaluation strategies required
Key Responsibilities
Design data slices to reveal model failure modes across domains
Build and refine evaluation rubrics and reward signals for RLHF and RLVR pipelines
Develop quantitative methods to measure dataset quality, diversity, and downstream impact
Create and manage real-world and synthetic data pipelines
Work with research teams to translate training objectives into data and evaluation specifications
Technical Skills Required
Machine Learning Data Collection Strategies Evaluation Rubrics
Benefits & Perks
Base salary of $260,000 to $290,000 annually
Visa sponsorship available

Job Description

About the Role

Build datasets, evaluation rubrics, and reward signals that help improve large language models. You will work with AI research teams to test data-collection approaches, investigate model failure modes, and develop measurements that inform training runs.

What You'll Do

Design data slices that reveal meaningful model failure modes across areas such as finance, software, and enterprise workflows.

Build and refine evaluation rubrics and reward signals for RLHF and RLVR pipelines.

Model annotator behavior and run experiments to improve model capabilities.

Develop quantitative methods to measure dataset quality, diversity, and downstream impact.

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