Staff / Principal Applied AI Researcher (Agentic Search)

📋 Description

• Lead applied AI research across retrieval, ranking, and agentic search systems.
• Design multi-stage retrieval architectures for query understanding, rewriting, reranking, and
• Enable LLMs/AI agents to retrieve, evaluate, and reason over real-time web data.
• Build agent-native retrieval systems for machine-centric workflows.
• Develop LLM-integrated, knowledge-intensive retrieval systems and multi-step agent workflows.
• Translate research into production with engineering teams; optimize relevance, latency, and cost.

🎯 Requirements

• 8+ years in applied AI, ML, software engineering, or related field.
• Proven track record shipping ML/AI systems at scale.
• Deep expertise in search, IR, ranking, recommendation, AI assistants.
• Strong understanding of transformers, embeddings, LLM-based systems.
• Hands-on with LLM-integrated retrieval/knowledge-intensive systems.
• Experience designing evaluation frameworks and metrics for ML/AI systems.

🎁 Benefits

• Competitive compensation.
• Flexible, autonomous working environment.
• Career development and learning opportunities.
• Work on technically ambitious, high-impact AI projects.
• Exposure to cutting-edge research in agentic AI, IR, LLMs, ML at scale.
• Influence research direction, system architecture, and product strategy.