Staff Applied AI Researcher (Agentic Search)
Core
Shape the future of AI-powered information retrieval by developing next-generation search systems designed specifically for autonomous AI agents.
Role type
Staff Applied AI Researcher (Agentic Search)
Builds
Next-generation agentic search systems enabling AI agents to plan, retrieve, evaluate, and refine information from the web in real time.
Domain
AI Research / Information Retrieval / Large Language Models
Deliverable
production ML models
Required skills
Applied AI research, Information retrieval, Search technologies, Ranking systems, RAG assistants, Transformer architectures, Embedding models, LLM-integrated systems, Evaluation frameworks, Python
Preferred skills
Agentic AI systems, Reinforcement learning post-training, Vision-language models
Technologies
Python, Transformers, Embedding models, LLMs
Responsibilities
Lead applied AI research and define technical direction of retrieval and ranking systems; Design and evolve multi-stage retrieval architectures; Develop agent-native search capabilities supporting 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 and optimize trade-offs between relevance, latency, reliability, and cost; Partner with engineering teams to deploy and scale AI search capabilities; Mentor researchers and engineers.
