# Applied Research Engineer

**Company:** [Drata](https://hotfix.jobs/companies/drata)
**Location:** San Francisco, CA
**Role:** ML Engineering
**Salary:** $145k – $196k/yr
**Experience:** 3+ years
**Skills:** Python, RAG, Information Retrieval, NLP, Embedding Models, Vector Databases, Evaluation Metrics, A/B Testing, Cross-Encoders, Learning-To-Rank
**Posted:** 2026-05-26

> Drive the quality of Drata's AI systems through experimentation and applied research on RAG, agents, and information retrieval. Own evaluation frameworks and translate validated approaches into production with AI and Software Engineers.

## Job Description

## What you'll do
- 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

## What you'll bring
- 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

## Bonus
- Experience with compliance, legal, or document-heavy domains
- Publications or contributions in IR, NLP, or RAG evaluation

## Compensation & Benefits
- Competitive base salary: $145,200 - $196,400
- Stock equity (RSUs)
- Up to 100% employer-paid medical, dental, and vision premiums
- 401(k) plan, company-paid life and disability insurance
- Paid Parental Leave (after 6 months)
- Kindbody fertility and family-building benefits
- Generous annual professional and personal development stipends
- Flexible vacation policy and paid holidays

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**Canonical:** https://hotfix.jobs/jobs/f6491472-23e9-4082-9b61-f6bc3a375b48