Applied Research Engineer

About the role

The Applied Research Engineer will drive the quality and effectiveness of Drata's AI systems through rigorous experimentation, evaluation, and applied research. This role emphasizes experimentation and rigor over production engineering.

Responsibilities

• Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, semantic routing
• Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements ↔ evidence)
• Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and structured prediction
• Build and maintain evaluation frameworks: golden datasets, automated quality metrics, regression detection
• Implement and tune ranking/reranking systems: cross-encoders, LLM-based rerankers, learning-to-rank, custom scoring functions
• Run experiments to validate hypotheses and quantify improvements before production rollout
• Debug failure modes and build error taxonomies across retrieval, reasoning, and generation
• Collaborate with AI and Software Engineers to hand off validated approaches for productionization
• Stay current on applied research in RAG, agents, LLM evaluation, and relevance modeling; bring innovations into the product

Requirements

• 3+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems
• 1+ years of hands-on experience building or contributing to production AI/ML systems
• Strong foundation in information retrieval: dense and sparse retrieval, embedding models, search relevance
• Experience with RAG systems: chunking strategies, vector databases, retrieval optimization
• Proficiency in evaluation methodology: metrics design, golden dataset creation, A/B testing, statistical significance
• Strong Python skills and comfort with notebook-driven research workflows
• Experience communicating research findings to engineering teams and translating insights into actionable improvements

Qualifications

• Experience with compliance, legal, or document-heavy domains
• Publishations or contributions in IR, NLP, or RAG evaluation

Skills

• Applied Research
• Data Science
• Machine Learning
• Natural Language Processing
• Information Retrieval
• Knowledge Systems

Benefits

• Stock Equity
• Health & Wellness
• Financial Well-being
• Family Support
• Growth & Development
• Time Off & Flexibility

Pay

$145,200 - $196,400

Schedule

Full-time