Principal Applied Data Scientist - Search and Browse (NLP, Vector Search, LLMs)
Core
Define long-term technical vision and architecture for large-scale semantic search, retrieval, ranking, and GenAI systems powering Target's e-commerce discovery.
Role type
Principal Applied Data Scientist (Search & Browse)
Builds
AI-native commerce discovery systems, semantic retrieval, conversational search, and agentic AI platforms for retail.
Domain
Retail E-commerce, Search & Recommendation, Generative AI
Deliverable
production ML models | product features | infrastructure
Required skills
semantic retrieval, vector search, RAG architectures, transformers, LLMs, multi-stage ranking systems, Python programming, ML infrastructure design, cross-functional leadership, strategic planning, system reliability optimization
Preferred skills
experience with VertexAI, conversational commerce, agentic AI, zero-shot discovery, enterprise-scale system operations
Technologies
VertexAI, Python, LLMs, RAG, transformers
Responsibilities
Define technical roadmap for search and AI-driven discovery systems, lead architecture strategy for retrieval and ranking, drive innovation in GenAI and agentic AI, establish scalable ML architecture patterns, mentor lead scientists, influence executive stakeholders on technical direction
Seniority
Principal, strategy & mentorship
