# Director of Research, DataLab

**Company:** [Protege](https://hotfix.jobs/companies/protege)
**Location:** Remote
**Role:** AI Research
**Skills:** Ai Research, Machine Learning, Llm Evaluation, Dataset Quality Evaluation, Synthetic Data, Experimentation Frameworks, Research Strategy, Team Leadership, Foundation Models, Privacy-Preserving Methodologies
**Posted:** 2026-05-23

> Lead Protege's DataLab research organization, defining strategy for AI training data quality, evaluation systems, and marketplace optimization while managing researchers and partnering with Product, Engineering, and GTM.

## Job Description

## Responsibilities
- Define and lead the research strategy for Protege's DataLab, aligning experimentation with company priorities and product direction
- Partner closely with Product, Engineering, and GTM teams to identify high-value research opportunities tied to AI data quality, evaluation, and marketplace performance
- Design and oversee experiments that evaluate dataset quality, model performance, synthetic data workflows, and privacy-preserving methodologies
- Build scalable systems for benchmarking, labeling quality analysis, and training data evaluation across multiple AI modalities
- Serve as a customer-facing research partner to GTM, representing DataLab in sales, technical discovery, delivery, and customer strategy conversations
- Translate ambiguous technical questions into clear research frameworks, measurable hypotheses, and actionable recommendations
- Publish internal research findings that directly influence product decisions, customer strategy, and platform capabilities
- Lead, manage, and scale a high-performing team of researchers and data scientists, driving execution, technical excellence, and career development
- Establish operational rigor around experimentation, reproducibility, and research documentation
- Represent Protege externally through technical conversations with customers, partners, and the broader AI ecosystem
- Stay at the forefront of advancements in foundation models, evaluation methodologies, data infrastructure, and AI alignment research

## Requirements
- Led impactful research initiatives in AI, machine learning, data infrastructure, or applied research environments where outcomes influenced product or business strategy
- Built and managed high-performing research teams that operated with autonomy, technical rigor, and fast execution cycles
- Experience partnering directly with customers, GTM teams, or external stakeholders in applied technical settings
- Developed frameworks for evaluating model performance, dataset quality, synthetic data, or large-scale experimentation systems
- Experience operating in ambiguous, fast-moving environments where priorities evolved quickly
- Strong ability to communicate complex technical findings to both technical and non-technical audiences
- Demonstrated ownership of cross-functional initiatives spanning research, engineering, product, and go-to-market teams
- Track record of translating research into practical systems, tools, or customer-facing impact
- Experience working with modern AI systems, foundation models, LLM evaluation workflows, or privacy-centric data methodologies
- High judgment, strong prioritization skills, and comfort making decisions with incomplete information

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