Staff / Principal Applied AI Researcher (Agentic Search)

📋 Description

• Drive applied research and technical direction across retrieval, ranking, and agentic search
• Design and evolve multi-stage retrieval architectures covering query understanding, query
• Develop approaches that enable LLMs and AI agents to retrieve, evaluate, and reason over constantly
• Design agent-native retrieval systems optimized for machine consumption and complex downstream AI
• Build systems in which LLMs can iteratively plan, query, refine, evaluate, and reason over
• Develop retrieval and ranking approaches capable of supporting multi-step, agent-driven workflows

🎯 Requirements

• 8+ years of professional experience in applied AI, machine learning, software engineering, or a
• Proven track record of designing and shipping machine learning or AI systems into production at
• Deep expertise in search, information retrieval, ranking, recommendation systems, AI assistants, or
• Strong understanding of modern deep learning techniques, particularly transformers, embeddings, and
• Hands-on experience developing LLM-integrated, knowledge-intensive, retrieval-based, or similar AI
• Experience designing evaluation frameworks, benchmarks, and metrics for machine learning or AI

🎁 Benefits

• Competitive compensation.
• Flexible working environment with significant ownership and autonomy.
• Career development and continuous learning opportunities.
• Opportunity to work on technically ambitious and high-impact AI projects.
• Exposure to cutting-edge research across agentic AI, information retrieval, LLMs, and large-scale
• Opportunity to influence research direction, system architecture, and product strategy.