Staff Applied AI Researcher (Agentic Search)
Core
Develop next-generation search systems for autonomous AI agents, enabling real-time planning, retrieval, and evaluation of information from the web.
Role type
Staff Applied AI Researcher (Agentic Search)
Builds
AI-powered search infrastructure for autonomous agents
Domain
AI Research / Information Retrieval / Search Technologies
Deliverable
production ML models
Required skills
Applied AI research, Information retrieval, Ranking systems, RAG assistants, Transformer architectures, Embedding models, LLM-integrated systems, Evaluation frameworks, Python programming, Research publications
Preferred skills
Agentic AI systems, Reinforcement learning post-training
Technologies
Python, LLMs, Transformers, Embedding models
Responsibilities
Lead applied AI research and define technical direction for retrieval and ranking systems; Design and evolve multi-stage retrieval architectures; Develop agent-native search capabilities for iterative planning and reasoning; Lead experimentation with advanced retrieval techniques; Train and optimize ranking and retrieval models for agent-driven workflows; Develop approaches for grounding LLMs in real-time web data; Collaborate with evaluation teams to develop new metrics; Analyze trade-offs between relevance, latency, reliability, and cost; Partner with engineering teams to deploy and scale AI search capabilities; Mentor researchers and engineers.
Seniority
Staff, hands-on IC with technical leadership
