Target

Senior Director of Search (Data Sciences & Engineering) at Target, leading a global organization of 60+ to build and evolve the end-to-end Search ecosystem. The role focuses on technical strategy, AI innovation, and operational excellence for query understanding, semantic retrieval, ranking systems, relevance AI, search platform architecture, evaluation frameworks, and conversational/agentic search capabilities. Key responsibilities include defining technical vision, leading the transition to agentic search, advancing AI capabilities (embeddings, transformers, RL, LLM reasoning), building AI systems for intent understanding and RAG, establishing evaluation frameworks, driving responsible AI and governance, and partnering with product and engineering leadership. Requires advanced degree, 16+ years of experience in production ML/AI systems, deep expertise in Search/IR, and proven leadership experience.

Principal Data Scientist role focused on designing, developing, and deploying generative AI solutions, including working with Multimodal LLMs and fine-tuning them. The role involves analyzing large datasets, contributing to research, and collaborating with AI/ML engineers to productionize GenAI solutions for retail use cases.

Senior Data Scientist role focused on designing, developing, deploying, and maintaining data science models and tools, with a strong emphasis on Generative AI and Multimodal LLMs. The role involves contributing to research, enhancing model performance, fine-tuning LLMs, and collaborating with AI/ML engineers to build GenAI solutions for retail applications.

Lead Operations Research Scientist at Target, focusing on supply chain optimization using advanced mathematical techniques, AI, ML, and simulations. The role involves problem structuring, data analysis, model development, and project delivery to improve efficiency and profitability.

Senior Engineer role focused on integrating LLMs and GenAI into core applications, building systems for AI reliability, and developing agentic frameworks for automation. Requires strong Java backend experience, microservices, and cloud platforms, with a focus on scalable and resilient systems.

This role focuses on applying operations research, machine learning, and AI techniques to solve complex supply chain problems, involving data analysis, model development, and insight generation for a large retail company.

Lead Engineer role focused on integrating GenAI and LLMs into core applications, building agentic frameworks, and improving AI reliability. Requires strong backend engineering skills in Java/Python, microservices, and cloud platforms, with an emphasis on building scalable and resilient AI-powered systems.

Product Manager for an Enterprise AI Platform team focused on AI Context Services. The role involves evolving platform services for GenAI and agentic applications, including Enterprise Search, RAG, Memory, and Connectors. The goal is to build an Enterprise Context Graph for context-aware intelligence. Responsibilities include owning product strategy, roadmap, discovery, stakeholder alignment, and driving adoption.

Lead Data Scientist for the Content Creation team, focusing on building and deploying AI solutions using GenAI, computer vision, and traditional ML for marketing and site content use cases. Responsibilities include end-to-end ownership of algorithmic solutions, from data understanding and feature engineering to model development, validation, testing, and production deployment. The role involves collaborating with cross-functional teams, mentoring junior members, and driving technical strategy.

Senior Engineer role focused on integrating LLMs and GenAI features into core applications, building agentic frameworks, and improving AI reliability within an enterprise retail context. Requires strong backend development skills in Java/Python, microservices, and cloud technologies, with a focus on AI integration and automation.

Lead Engineer responsible for integrating LLMs and Generative AI into core applications, building and scaling agentic frameworks, and implementing safeguards for AI reliability within an enterprise platform.

Principal Engineer role focused on building and scaling agentic AI capabilities within the Merchandising portfolio at Target. This involves owning the technical strategy for AI/agentic features, architecting cloud-native systems, designing agent orchestration flows, delivering production LLM solutions with measurable outcomes, establishing evaluation and quality gates, implementing safety controls, and enabling platform adoption at scale. The role requires influencing cross-team technical direction and mentoring engineers.

This role focuses on designing, building, and integrating systems for e-commerce search, leveraging NLP, deep learning, classical ML, and LLMs to improve query understanding, ranking, relevance, and external search capabilities. The goal is to develop a multi-year vision for search on Target.com.

Sr AI Engineer role focused on AdTech, involving the definition, development, and integration of modules for algorithmic decision making within an ad serving tech platform. The role requires expertise in machine learning, probability theory, statistics, optimization, deep learning, NLP, or computer vision, with a focus on owning the design and implementation of algorithmic solutions from data understanding to production deployment. Responsibilities include driving problem statements, defining metrics, evaluating model tradeoffs, developing data pipelines, articulating technical strategy, and mentoring junior team members.

Lead Operations Research Scientist at Target, focusing on supply chain network optimization. This role involves developing and applying advanced operations research techniques, AI, and machine learning to solve complex business challenges, including simulations, scenario analyses, and optimization methods. Requires strong programming skills (Python, PySpark, R, SQL), experience with large datasets, and working with LLMs and modern ML frameworks. The role emphasizes stakeholder engagement, problem framing, data analysis, and effective communication of insights.