Research Engineers, Data

Distyl is hiring Research Engineers, Data to build data systems that support reliable AI workflows in enterprise environments. The role develops data pipelines, quality frameworks, and feedback strategies, and partners with research, engineering, and customer teams to improve AI system performance in production.

Responsibilities

• Design and build data systems that power reliable AI workflows across enterprise environments
• Develop pipelines for collecting, cleaning, transforming, labeling, and evaluating domain-specific data used by AI systems
• Create data quality frameworks that identify coverage gaps, ambiguity, drift, duplication, leakage, and other failure modes
• Build tools and workflows that help teams turn raw customer data into usable context for retrieval, evaluation, reasoning, and execution
• Partner with AI Researchers and AI Engineers to understand how data quality affects system behavior and production outcomes
• Develop synthetic data, annotation, and feedback-loop strategies to improve system performance in areas where real-world data is sparse or noisy
• Analyze customer workflows and datasets to determine what information AI systems need, where that information should come from, and how it should be represented
• Communicate clearly with internal teams and customer stakeholders about data assumptions, limitations, risks, and tradeoffs

Benefits

• Meaningful equity
• 100% coverage of medical, dental, and vision insurance for employee and dependents
• Flexible time off
• Access to pre-tax HSA, FSA, and commuter accounts
• 401(k)
• Financial coaching resources
• Physical fitness, mental well-being, and fertility and family-building benefits through Carrot
• Complimentary in-office lunches and snacks
• Access to state-of-the-art AI models and generous usage of modern AI tools
• Ownership of high-impact projects across top enterprises
• A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence
• Hybrid collaboration model with 3+ days per week (Tuesday–Thursday) in-office

Company

• Enterprise AI transformation design and implementation
• San Francisco, California, USA
• https://distyl.ai/
• Founded in 2022
• 51-200 employees

Qualifications

• Experience Building Data Systems for AI: You have built data pipelines, evaluation datasets, labeling workflows, retrieval corpora, or similar systems that improve model or agent behavior
• Strong Data Engineering Fundamentals: You write clean Python and SQL, understand data modeling and pipeline reliability, and can build systems that are maintainable under production constraints
• Research-Oriented Builder: You are comfortable investigating how data quality, structure, and representation affect AI system performance
• AI-Native Working Style: You use AI tools daily to accelerate coding, analysis, debugging, exploration, and workflow automation
• Comfort with Ambiguous Data: You can reason through messy enterprise datasets, incomplete documentation, conflicting business definitions, and changing requirements
• Bias Towards Measurement: You prefer to make data quality and system behavior observable through concrete metrics, evaluations, and experiments
• Customer Environment Readiness: You can work directly with customer teams to understand their data, ask precise questions, and explain tradeoffs clearly
• Ownership Mentality: You take responsibility for whether the data layer enables the AI system to deliver reliable value in production

Required skills

• AI Data Systems, Data Engineering, Data Labeling Workflows, Data Modeling, Data Pipelines, Data Quality, Evaluation Datasets, Production System Reliability, Python, Retrieval Corpora, SQL

Experience

• Mid level