Research Engineer, Data

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

Requirements

• Experience building data pipelines, evaluation datasets, labeling workflows, retrieval corpora, or similar systems that improve model or agent behavior
• Strong data engineering fundamentals: clean Python and SQL, data modeling, pipeline reliability, maintainable production systems
• Research-oriented builder comfortable investigating how data quality, structure, and representation affect AI system performance
• Use AI tools daily to accelerate coding, analysis, debugging, exploration, and workflow automation
• Comfort reasoning through messy enterprise datasets, incomplete documentation, conflicting business definitions, and changing requirements
• Bias towards measurement: make data quality and system behavior observable through concrete metrics, evaluations, and experiments
• Ability to work directly with customer teams to understand their data, ask precise questions, and explain tradeoffs clearly
• Ownership mentality for whether the data layer enables the AI system to deliver reliable value in production

Compensation and Benefits

• Base salary range: $150,000 – $250,000 (depending on experience, location, and level)
• Meaningful equity
• 100% covered medical, dental, and vision for employees and dependents
• 401(k) with additional perks (e.g., commuter benefits, in-office lunch)
• Access to state-of-the-art models, generous usage of modern AI tools, and real-world business problems
• Ownership of high-impact projects across top enterprises
• Mission-driven, fast-moving culture that prizes curiosity, pragmatism, and excellence