Drata

1 month ago

Staff Applied Research Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Lead research-driven development of AI systems for compliance with a focus on retrieval, reasoning, and evaluation frameworks. Design GenAI workflows, evaluate information access strategies, and collaborate with AI/Software Engineers to productionize validated approaches, ensuring high-quality, trustworthy AI performance in a fast-paced, hybrid Bay Area environment.

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, structured retrieval, tool use, and multi-step workflows
•Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements)
•Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and weak supervision
•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

Pay and Benefits

Salary: USD 220,800 - 298,800 annually

Equity and Bonus:Equity

Perks:Equity401kHealth InsuranceParental LeaveLearning BudgetTime OffPaid Leave

Key Requirements

•10+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems
•2+ 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 analysis

Experience:10+ yearsNLPInformation retrievalKnowledge systems

Skills:PythonNLPInformation retrievalRAGLLMVector databasesEvaluation metricsA/B testingCross-encoderRanking

Languages:English

Tech Stack:PythonLLMRAGVector databasesCross-encodersRankingA/B testingNotebook-driven

Company Brief

Drata

Provides a continuous security and compliance automation platform to help companies achieve and maintain frameworks such as SOC 2, ISO 27001, HIPAA, and GDPR through automated evidence collection and monitoring. ([drata.com](https://drata.com/blog/fy25-momentum?utm_source=openai))

Industry: RegTech

Company Size: Large (251 to 1,000 employees)

Revenue: USD 100M to 250M

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Diego, United States

Founded: 2020

Glassdoor: 3.3

Website LinkedIn Glassdoor

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Drata

1 month ago

Staff Applied Research Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Research & Scientific (R&D)

Key Responsibilities

•Design and evaluate information access + reasoning strategies across RAG, agents, and classic ML: chunking, embedding models, hybrid search, metadata filtering, structured retrieval, tool use, and multi-step workflows
•Prototype GenAI workflows (including agentic systems) that map and reason over compliance objects (controls ↔ risks ↔ requirements)
•Explore ML + probabilistic approaches where GenAI is not the best fit: classifiers, ranking models, graph/link prediction, calibration, and weak supervision
•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

Pay and Benefits

Salary: USD 220,800 - 298,800 annually

Equity and Bonus:Equity

Perks:Equity401kHealth InsuranceParental LeaveLearning BudgetTime OffPaid Leave

Key Requirements

•10+ years of experience in applied research, data science, or ML with a focus on NLP, information retrieval, or knowledge systems
•2+ 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 analysis

Experience:10+ yearsNLPInformation retrievalKnowledge systems

Skills:PythonNLPInformation retrievalRAGLLMVector databasesEvaluation metricsA/B testingCross-encoderRanking

Languages:English

Tech Stack:PythonLLMRAGVector databasesCross-encodersRankingA/B testingNotebook-driven

Company Brief

Drata

Industry: RegTech

Company Size: Large (251 to 1,000 employees)

Revenue: USD 100M to 250M

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series C

Headquarters: San Diego, United States

Founded: 2020

Glassdoor: 3.3

Website LinkedIn Glassdoor