AI Data Systems Engineer — Production Pipelines & Equity

Distyl; San Francisco (CA); Hybride; USD 150 000 - 250 000; Plein temps

Avantages offerts par ce poste

Meaningful equity

Comprehensive benefits package

100% medical/dental/vision for you and

Flexible time off

401(k) and financial planning options

Wellness benefits (Carrot)

Résumé du poste

Distyl is seeking Research Engineers to bridge frontier AI research and production systems, building data pipelines, data quality frameworks, and tooling to support enterprise AI workloads. You will collaborate with AI Researchers, AI Engineers, and customer stakeholders to design scalable data systems, synthetic data strategies, and evaluation methods for model behavior.

The role is hybrid with in-office days in San Francisco and New York.

Qualifications

• Built data pipelines, evaluation datasets, labeling workflows, retrieval corpora, or similar systems that improve model or agent behavior
• Strong data engineering fundamentals: python/sql, data modeling, pipeline reliability
• Research-oriented approach to how data quality affects AI system performance
• AI-native working style: using AI tools to accelerate coding, analysis, debugging, exploration, and automation
• Comfort working with messy enterprise datasets and changing requirements
• Bias toward measurement: use metrics and experiments to judge data quality and system behavior
• Customer environment readiness: ability to work with customer data and explain tradeoffs
• Ownership mentality: accountable for data layer enabling reliable AI in production

Responsabilités

• Design and build data systems powering reliable AI workflows across enterprise environments
• Develop pipelines for collecting, cleaning, transforming, labeling, and evaluating domain-specific data
• Create data quality frameworks to identify coverage gaps, ambiguity, drift, duplication, leakage, and other failures
• Build tools and workflows to turn raw customer data into usable context for retrieval, evaluation, reasoning, and execution
• Partner with AI Researchers and Engineers to understand data quality impact on system behavior and outcomes
• Develop synthetic data, annotation, and feedback-loop strategies to improve performance where real data is scarce
• Analyze customer workflows to determine information needs and representations for AI systems
• Communicate data assumptions, limitations, risks, and tradeoffs clearly to internal and customer teams

Connaissances

Experience Building Data Systems forAI

Data Engineering Fundamentals

Research-Oriented Builder

AI-Native Working Style

Ambiguous Data Handling

Measurement-Driven

Customer Environment Readiness

Ownership mentality

Python

SQL

Outils

Python

SQL

Description du poste

Distyl is seeking Research Engineers to bridge frontier AI research and production systems, building data pipelines, data quality frameworks, and tooling to support enterprise AI workloads. You will collaborate with AI Researchers, AI Engineers, and customer stakeholders to design scalable data systems, synthetic data strategies, and evaluation methods for model behavior.

The role is hybrid with in-office days in San Francisco and New York.