Research Engineers, Data

Distyl; San Francisco (CA); Hybrid; USD 150,000 - 250,000; Full time

Benefits offered by this job

Meaningful equity

Comprehensive benefits package

100% medical/dental/vision for you and

Flexible time off

401(k) and financial planning options

Wellness benefits (Carrot)

Job summary

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

Responsibilities

• 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

Skills

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

Tools

Python

SQL

Job description

About Distyl AI

Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations.

About Distyl AI

Distyl is an applied AI technology company partnering with the world’s most ambitious institutions to rearchitect critical operations for the frontier of AI. Our customers include the largest companies in telecom, healthcare, insurance, manufacturing, consumer goods, and global social organizations. We research and deploy technologies that power AI-native operations - both for our partners and for Distyl itself. Our work spans research into self-constructing systems, the development of the most reliable execution of AI systems, and products that transform mission-critical workflows. As a result, Distyl's technologies affect some of the world's largest operations - from hundreds of millions of consumer interactions to tens of millions of supply chain transactions and millions of patient journeys. Distyl is backed by leading investors including Lightspeed Venture Partners, Khosla Ventures, Coatue, DST Global, and the board-members of 20+ F500s.

What We Are Looking For

At Distyl, Research Engineers build the bridge between frontier AI research and production systems that deliver real business value. This role is for engineers who are excited to investigate how AI systems should be designed, rapidly prototype new ideas, and turn promising concepts into reliable systems that work inside real customer environments. Research Engineers operate at the intersection of applied research, systems engineering, and customer-facing deployment. They design and implement compound AI systems, run experiments to understand system behavior, build evaluation frameworks, and collaborate closely with AI Researchers, AI Engineers, and customer stakeholders. Their work is not limited to demos or isolated prototypes: they help turn new techniques into robust systems that can be measured, operated, and improved in production.

Key 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

Who You Are

• 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

What We Offer

• The base salary range for this role is $150K - $250K, depending on experience, location, and level. In addition to base compensation, this role is eligible for meaningful equity, along with a comprehensive benefits package
• 100% coverage of medical, dental, and vision insurance for employee and dependents
• Flexible time off
• Retirement and financial planning benefits, including access to pre-tax HSA, FSA, and commuter accounts, 401(k), and financial coaching resources
• Comprehensive wellness benefits, including physical fitness, mental well-being, and fertility and family-building benefits through Carrot
• Complimentary in-office lunches and snacks provided
• Access to state-of-the-art AI models, generous usage of modern AI tools, and real-world business problems
• Ownership of high-impact projects across top enterprises
• A mission-driven, fast-moving culture that values curiosity, pragmatism, and excellence

Distyl has offices in San Francisco and New York. This role follows a hybrid collaboration model with 3+ days per week (Tuesday-Thursday) in-office.

We believe diverse perspectives make our work stronger and more impactful. We are an equal opportunity employer and evaluate all applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, disability, veteran status, or any other legally protected characteristic. We encourage candidates from all backgrounds to apply.