Staff / Principal Applied AI Researcher (Agentic Search)

📋 Description

• Drive applied AI research and technical direction across retrieval and ranking systems for
• Design and evolve multi-stage retrieval architectures, including query understanding, query
• Develop approaches for grounding LLMs in real-time web data while maintaining quality, scalability
• Build and refine systems where LLMs can plan, query, evaluate, refine, and reason over retrieved
• Define new evaluation frameworks, metrics, and experimentation methodologies for agentic systems
• Lead experimentation with modern retrieval technologies, including embeddings, hybrid search

🎯 Requirements

• 8+ years of experience in applied AI, machine learning, or software engineering.
• Proven track record of designing and shipping ML or AI systems into production at meaningful scale.
• Deep expertise in search, information retrieval, ranking, recommendation systems, assistants, or
• Strong understanding of modern deep learning, particularly transformer architectures and embeddings.
• Experience building LLM-integrated, knowledge-intensive, or retrieval-augmented systems.
• Practical experience designing evaluation frameworks and meaningful metrics for machine learning or

🎁 Benefits

• Competitive compensation.
• Career growth and ongoing learning opportunities.
• High levels of flexibility, autonomy, and ownership.
• Opportunity to work on impactful applied AI projects at significant scale.
• Collaborative and innovative working environment.
• International team with highly experienced AI, engineering, and research professionals.