Principal Applied Data Scientist - Search and Browse (NLP, Vector Search, LLMs)

What you'll do

• Define long-term technical vision and organizational roadmap for search, browse, and AI-driven discovery systems.
• Lead architecture strategy for large-scale retrieval, ranking, semantic search, and GenAI systems at massive scale.
• Drive innovation in transformers, LLMs, RAG architectures, multi-stage ranking systems, personalization, conversational commerce, and agentic AI.
• Architect search and retrieval systems for integration with external LLM and agentic search ecosystems.
• Establish scalable ML architecture patterns, experimentation standards, and operational best practices across multiple teams.
• Mentor lead scientists and technical leaders while representing the organization in executive reviews.

What we're looking for

• PhD or MS in Computer Science, Statistics, Applied Mathematics, Physics, or related quantitative discipline
• 8+ years of industry experience building and scaling ML systems for Search, Recommendation, Personalization, Ads, or AI platforms
• Strong experience with semantic retrieval, vector search, RAG systems, conversational search, and agentic AI systems
• Deep expertise in retrieval/ranking architectures, recommendation systems, NLP/LLMs, experimentation, and ML infrastructure (VertexAI)
• Proven ability to define architecture and long-term strategy for large-scale production AI systems
• Experience operating large-scale online systems with strict latency, scalability, reliability, and infrastructure cost requirements
• Strong track record driving measurable business impact through ML innovation