Target

Lead Data Scientist for Competitive Intelligence team focused on competitor product matching using NLP, deep learning, transformers, and GenAI/Agentic AI (RAG, LLM agents, tool use). Role involves designing, developing, and productionizing AIML systems, owning technical direction, architecting end-to-end solutions, and mentoring a team. Requires expertise in modern ML, GenAI, Agentic AI, and production AIML systems.

Principal AI Engineer focused on building and scaling advanced AI capabilities, including agentic and LLM-powered systems, for enterprise-wide automation and optimization. The role involves deep technical leadership, end-to-end solution design, deployment, and establishing robust engineering practices for production AI applications.

Lead Engineer for GenAI at Target, focusing on designing and implementing autonomous AI agents with multi-step reasoning, task planning, and tool usage. The role involves leading development of agent orchestration frameworks, applying LLMs, building evaluation systems, implementing safety mechanisms, and creating data pipelines for training and inference. It emphasizes productionizing GenAI capabilities and adopting emerging technologies within an enterprise retail context.

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 focused on Malware Reverse Engineering, leveraging AI-augmented analysis to triage samples, validate machine-generated analysis, and investigate complex malware. The role involves developing reverse engineering skills, analyzing attacker tradecraft, and translating insights into durable detections. Responsibilities include reviewing AI analysis results, identifying inaccuracies, refining analysis, triaging large sample sets, performing targeted reverse engineering on critical code paths, analyzing obfuscation techniques, understanding exploit patterns, and contributing to detection logic development using tools like YARA. The role also involves working with automated analysis pipelines and using Python scripting to enhance tooling.

Sr Data Scientist role focused on Global Supply Chain and Logistics, leveraging operations research, simulation, and machine learning to develop and deploy optimization and ML algorithms at scale. Requires strong computer science fundamentals, experience with production deployments, and proficiency in mathematical modeling and programming languages.

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 ML, LLMs, and NLP to improve search ranking within a consumer domain. The primary responsibility is to deploy end-to-end ML models and algorithms into production, with a secondary focus on the inference path. The role requires strong Python programming, experience with MLOps, SQL, and knowledge of search indexing and ranking.

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 ML Engineer for Target's personalization and recommendation systems on Target.com and the Target App. Focus on designing, implementing, and optimizing production ML solutions, including data pipelining, model optimization, deployment, and API design. Requires strong Python, ML frameworks, cloud ML services, distributed training, serving frameworks, and CI/CD experience. Will mentor junior team members and collaborate with cross-functional teams.

Principal Engineer role focused on defining and driving unified architecture for a store optimization platform. This involves leading the evolution towards intelligent task orchestration, establishing multi-objective optimization frameworks, and ensuring end-to-end system integrity. The role requires embedding observability, guardrails, and explainability into AI-driven systems, and partnering across teams to drive scalable platform design. Experience building and productionizing AI/GenAI systems, including LLMs, RAG, prompting, evaluation, and guardrails, is critical.

Lead Engineer for Threat Hunting & Countermeasures role at Target, focusing on proactive, hypothesis-driven threat hunting using large-scale security datasets, statistical methods, and machine learning. The role involves developing and operationalizing production-ready detections and countermeasures to identify novel or evasive threats, and collaborating with various security teams.

Senior Engineer role focused on integrating AI/ML capabilities into cybersecurity operational processes and applications at Target. The role involves evaluating new AI technologies, prototyping, and developing AI-powered solutions, with a focus on LLMOps and production deployment.

Lead Engineer for Cybersecurity AI Activation and Engineering team, responsible for application architecture and designs for AI-powered capabilities within cybersecurity. Will evaluate new technologies, conduct research and proof-of-concept activities, and contribute to foundational AI/ML capabilities. Focus on LLMOps, solution reliability, and sustainability.

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.

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.

Lead Operations Research Scientist at Target, focusing on supply chain optimization using advanced mathematical techniques, AI, and machine learning. The role involves developing and applying these techniques to solve complex business challenges, working with large datasets, and collaborating with cross-functional stakeholders to deliver measurable impact.

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.