Applied Research Engineer

Drata

Applied Research Engineer driving quality and effectiveness of AI systems through rigorous experimentation. Collaborating with AI and Software Engineers to turn validated approaches into production-ready systems.

Posted 5/26/2026full-timeSan Francisco • California • 🇺🇸 United StatesMid-LevelSenior💰 $145,200 - $196,400 per yearWebsite

Tech Stack

Tools & technologies

Python

About the role

Key responsibilities & impact

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

What you’ll need

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

Benefits

Comp & perks

Up to 100% employer-paid premiums for medical, dental, and vision coverage for employees and their dependents
401(k) plan
Company-paid life and disability insurance
Paid Parental Leave policy after six months of employment
Generous annual stipends for professional and personal development
Flexible vacation policy and paid holidays

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills & Tools

information access strategiesreasoning strategieschunkingembedding modelshybrid searchmetadata filteringsemantic routingranking modelsevaluation frameworksPython

Soft Skills

collaborationcommunicationproblem-solvingdebugginghypothesis validation