Staff / Principal Applied AI Researcher (Agentic Search)

📋 Description

• Drive applied research across retrieval, ranking, and agentic search systems.
• Design multi-stage retrieval architectures for query understanding and refinement.
• Enable LLMs and AI agents to reason over real-time web data.
• Build agent-native retrieval systems for machine workflows.
• Let LLMs iteratively plan, query, refine, and reason over data.
• Develop retrieval and ranking for multi-step, agent-driven tasks.

🎯 Requirements

• 8+ years in applied AI, ML, or related field.
• Proven production ML/AI system deployment at scale.
• Deep expertise in search, IR, ranking, or recommendations.
• Strong DL knowledge: transformers, embeddings, LLMs.
• Hands-on with LLM-integrated or knowledge-intensive systems.
• Experience with evaluation frameworks and metrics.

🎁 Benefits

• Competitive compensation.
• Flexible, autonomous working environment.
• Career development and learning opportunities.
• Work on ambitious AI projects with impact.
• Exposure to cutting-edge agentic AI and ML systems.
• Influence research direction and product strategy.