Senior Applied Research Engineer

📋 Description

• Design and evaluate information access and reasoning across RAG, agents, and ML.
• Prototype GenAI workflows mapping over compliance objects (controls ↔ risks ↔ requirements ↔ evidence).
• Explore ML and probabilistic approaches where GenAI isn't best: classifiers, ranking, graph/link prediction.
• Build and maintain evaluation frameworks: golden datasets, metrics, regression detection.
• Implement and tune ranking/reranking: cross-encoders, LLM rerankers, learning-to-rank.
• Run experiments to validate hypotheses and quantify improvements before production rollout.

🎯 Requirements

• 5+ years in applied research, data science, or ML focusing on NLP
• 2+ years building or contributing to production AI/ML systems
• Strong foundation in information retrieval: dense/sparse retrieval, embeddings
• Experience with RAG: chunking strategies, vector databases, retrieval optimization
• Proficiency in evaluation methodology: metrics design, golden datasets, A/B testing
• Strong Python skills and notebook-driven research workflows

🎁 Benefits

• Shared equity to align you with company growth
• Health and wellness: employer-paid premiums for you and dependents
• Financial well-being: 401(k), life and disability insurance
• Parental Leave and family-building benefits
• Growth and development stipends and internal learning
• Flexible vacation, holidays, and time off