Principal Applied Data Scientist – Search and Browse, NLP, Vector Search, LLMs

Role Overview

• Define the 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 operating at massive scale
• Drive innovation across transformers, LLMs, RAG architectures, multi-stage ranking systems, personalization, conversational commerce, and agentic AI
• Architect search and retrieval systems for external LLM and agentic search ecosystem integration
• Define the future evolution of semantic retrieval, conversational search, and zero-shot discovery systems
• Influence organization-wide strategy across relevance, experimentation, evaluation, ML infrastructure, and AI product investments
• Lead highly ambiguous, multi-quarter initiatives involving Product, Engineering, Applied Science, Infrastructure, and executive stakeholders
• Establish scalable ML architecture patterns, experimentation standards, and operational best practices across multiple teams
• Drive foundational investments and technical direction across Search, Retrieval Infrastructure, and AI-powered discovery platforms
• Balance customer experience, business impact, system reliability, latency, scalability, and infrastructure cost at enterprise scale
• Mentor Lead scientists and technical leaders across the organization
• Represent the organization in executive reviews and drive alignment on major technical and product decisions
• Influence technical direction and investment priorities across multiple teams and organizations

Requirements

• 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 or agentic AI systems
• Deep expertise in retrieval/ranking architectures, recommendation systems, semantic search, NLP/LLMs, experimentation and ML infrastructure (VertexAI)
• Demonstrated Python programming and technical ML problem-solving skills
• Proven experience defining 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 understanding of retrieval/ranking system tradeoffs, experimentation strategy, and operational excellence
• Strong track record driving measurable business impact through ML innovation
• Experience leading cross-functional initiatives spanning multiple teams or organizations
• Ability to influence executive stakeholders and drive organizational technical direction
• Exceptional communication, technical leadership, strategic thinking, and mentoring skills

Tech Stack

• Python

Benefits

• Comprehensive health benefits and programs including medical, vision, dental, and life insurance
• 401(k)
• Employee discount
• Short term disability
• Long term disability
• Paid sick leave
• Paid national holidays
• Paid vacation