📋 Description

• Design and build data systems that power reliable AI workflows across enterprise environments
• Develop pipelines for collecting, cleaning, transforming, labeling, and evaluating domain-specific
• Create data quality frameworks that identify coverage gaps, ambiguity, drift, duplication, leakage
• Build tools and workflows that help teams turn raw customer data into usable context for retrieval
• Partner with AI Researchers and AI Engineers to understand how data quality affects system behavior
• Develop synthetic data, annotation, and feedback-loop strategies to improve system performance in

🎯 Requirements

• Experience Building Data Systems for AI: data pipelines, evaluation datasets, labeling workflows
• Strong Data Engineering Fundamentals: Python and SQL, data modeling, reliable pipelines
• Research-Oriented Builder: interest in data quality and AI system performance
• AI-Native Working Style: use AI tools to accelerate coding, analysis, debugging, exploration
• Comfort with Ambiguous Data: messy enterprise datasets, changing requirements
• Bias Towards Measurement: metrics, evaluations, experiments for data quality

🎁 Benefits

• The base salary range for this role is $150K – $250K, plus equity and benefits
• 100% coverage of medical, dental, and vision for employee and dependents
• Flexible time off and retirement/financial planning resources
• Wellness benefits, Carrot fertility/family-building benefits
• In-office lunches and snacks, state-of-the-art AI tools access
• Hybrid collaboration model with 3+ days in-office (Tue–Thu) in SF/NY offices