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

Principal Data Scientist – Search and BrowseWorking at Target means helping all families discover the joy of everyday life. We bring that vision to life through our values and culture. Learn more about Target here.A role with Applied Data Sciences team at Target means the chance to help develop and manage state of the art predictive algorithms that use data at scale to automate and optimize decisions at scale.

Whether you join our Search, RecSys, Supply Chain Optimization or Machine Learning teams, you'll be challenged to harness Target's impressive data breadth to build the algorithms that power solutions our partners in Marketing, Supply Chain Optimization, Network Security and Personalization rely on. Every Scientist on Target's Data Sciences team can expect modeling and data science, software/product development of highly performant code for Model Performance, and to elevate Target's culture and apply retail domain knowledge.The Search and Browse Applied Data Science team builds the foundational relevance, retrieval, ranking, and personalized search systems that power Target's Digital experience at scale. We are defining the future of AI-native commerce discovery across Search, Browse and emerging conversational shopping experiences.E-commerce Search is undergoing a massive transformation, and we are building the architecture to lead it.

We are solving some of the hardest problems in retail AI at a $10B+ commercial scale and 10K+ QPS, including:Architecting search and data systems for external LLM ingestion so our catalog wins in ChatGPT, Gemini, agentic commerce, and the next generation of AI-native discovery experiencesBuilding zero-shot and cold-start discovery systems for rapidly changing, seasonal retail inventorySolving natural language and long-tail search problems where conversational queries and traditional retrieval systems break against massive unstructured product catalogsEvolving multi-stage retrieval and ranking architectures that balance relevance quality, latency, scalability, and infrastructure efficiency at enterprise scaleWe are looking for pragmatic builders and technical leaders who thrive on shipping production systems at scale. Engineering excellence, sub-second latency, operational reliability, infrastructure economics, and seamless integration with core Retrieval and Ranking systems matter just as much as modeling sophistication.This role requires deep technical expertise, exceptional product judgment, and the ability to influence organizational strategy while driving measurable customer and business impact.As a Principal Data Scientist – Search and Browse you'll:Define the long-term technical vision and organizational roadmap for Search, Browse, and AI-driven discovery systemsLead architecture strategy for large-scale retrieval, ranking, semantic search, and GenAI systems operating at massive scaleDrive innovation across transformers, LLMs, RAG architectures, multi-stage ranking systems, personalization, conversational commerce, and agentic AIArchitect search and retrieval systems for external LLM and agentic search ecosystem integrationDefine the future evolution of semantic retrieval, conversational search, and zero-shot discovery systemsInfluence organization-wide strategy across relevance, experimentation, evaluation, ML infrastructure, and AI product investmentsLead highly ambiguous, multi-quarter initiatives involving Product, Engineering, Applied Science, Infrastructure, and executive stakeholdersEstablish scalable ML architecture patterns, experimentation standards, and operational best practices across multiple teamsDrive foundational investments and technical direction across Search, Retrieval Infrastructure, and AI-powered discovery platformsBalance customer experience, business impact, system reliability, latency, scalability, and infrastructure cost at enterprise scaleMentor Lead scientists and technical leaders across the organizationRepresent the organization in executive reviews and drive alignment on major technical and product decisionsInfluence technical direction and investment priorities across multiple teams and organizationsCore responsibilities of this job are articulated within this job description. Job duties may change at any time due to business needs.About you:PhD or MS in Computer Science, Statistics, Applied Mathematics, Physics or related quantitative discipline8+ years of industry experience building and scaling ML systems for Search, Recommendation, Personalization, Ads, or AI platformsStrong experience with semantic retrieval, vector search, RAG systems, conversational search or agentic AI systemsDeep expertise in retrieval/ranking architectures, recommendation systems, semantic search, NLP/LLMs, experimentation and ML infrastructure (VertexAI)Demonstrated Python programming and technical ML problem-solving skillsProven experience defining architecture and long-term strategy for large-scale production AI systemsExperience operating large-scale online systems with strict latency, scalability, reliability, and infrastructure cost requirementsStrong understanding of retrieval/ranking system tradeoffs, experimentation strategy, and operational excellenceStrong track record driving measurable business impact through ML innovationExperience leading cross-functional initiatives spanning multiple teams or organizationsAbility to influence executive stakeholders and drive organizational technical directionExceptional communication, technical leadership, strategic thinking, and mentoring skillsThis position will operate as a Hybrid/Flex for Your Day work arrangement based on Target's needs.

A Hybrid/Flex for Your Day work arrangement means the team member's core role will need to be performed both onsite at the Target HQ in Sunnyvale, CA or MN location the role is assigned to and virtually, depending upon what your role, team and tasks require for that day. Work duties cannot be performed outside of the country of the primary work location, unless otherwise prescribed by Target.Target will consider for employment qualified applicants with criminal histories in a manner consistent with the San Francisco and City of Los Angeles Fair Chance Ordinances.Application deadline is : 06/18/2026