San FranciscoFull TimeEngineering
Remotely
pythonsqldata qualitydata pipelinesaiannotationretrieval
Job Description
📋 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
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