Drata

1 month ago

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

Applied Research Engineer to drive the quality and effectiveness of AI systems through rigorous experimentation and applied research. Own the science behind how AI products retrieve, reason, and respond, collaborating with AI and Software Engineers to turn validated approaches into production-ready systems in a high-velocity hybrid 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, 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

Pay and Benefits

Equity and Bonus:Equity

Perks:Health Insurance401kRsusEquityParental LeaveLearning Budget

Key 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

Experience:3+ yearsInformation retrievalNLPAI/ML

Skills:PythonNLPInformation retrievalVector databasesEmbeddingsCross-encodersLLMRankingA/B testing

Tech Stack:PythonLLMVector databasesCross-encodersEmbedding modelsRetrievalInformation retrievalNLP

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

Loading job details...

Preparing the role view and application actions.

Drata

1 month ago

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, 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

Pay and Benefits

Equity and Bonus:Equity

Perks:Health Insurance401kRsusEquityParental LeaveLearning Budget

Key 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

Experience:3+ yearsInformation retrievalNLPAI/ML

Skills:PythonNLPInformation retrievalVector databasesEmbeddingsCross-encodersLLMRankingA/B testing

Tech Stack:PythonLLMVector databasesCross-encodersEmbedding modelsRetrievalInformation retrievalNLP

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