As a Fortune 50 company with more than 400,000 team members worldwide, Target is an iconic brand and one of America's leading retailers.
Joining Target means promoting a culture of mutual care and respect and striving to make the most meaningful and positive impact. Becoming a Target team member means joining a community that values different voices and lifts each other up. Here, we believe your unique perspective is important, and you'll build relationships by being authentic and respectful.
Overview about TII
At Target, we have a timeless purpose and a proven strategy. And that hasn’t happened by accident. Some of the best minds from different backgrounds come together at Target to redefine retail in an inclusive learning environment that values people and delivers world-class outcomes. That winning formula is especially apparent in Bengaluru, where Target in India operates as a fully integrated part of Target’s global team and has more than 4,000 team members supporting the company’s global strategy and operations.
Pyramid Overview
A role with Target Data Science & Engineering 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 Statistics, 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 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.
Team Overview
Target Data Sciences is offering an exciting opportunity to solve high-impact AI/ML problems in the retail item ecosystem. The Item Science team is focused on building intelligent capabilities that improve how products are onboarded, enriched, validated, discovered, and experienced across Target’s digital and operational channels.
Item data is the foundation of retail. It powers product discovery, search relevance, recommendations, SEO, PDP quality, vendor onboarding, merchandising decisions, and guest confidence. As Target continues to scale its digital and marketplace capabilities, we are looking for driven and passionate individuals with strong AI engineering, machine learning, GenAI, and production systems experience to help build the next generation of item intelligence platforms.
If you are that person, you can expect to be involved in:
Building scalable AI/ML capabilities for catalog management, item data quality, attribute enrichment, taxonomy prediction, and derived attributes.
Developing and productionizing solutions across GenAI, LLMs, computer vision, classical ML, deep learning, and agentic AI workflows.
About the role
As a Senior AI Engineer at Target, you will help build and scale production-grade AI/ML capabilities that power critical business workflows across the enterprise. You will partner closely with Data Science, Product, Engineering, and business teams to turn AI ideas and models into reliable, scalable, and high-performing systems.
This role is ideal for engineers who enjoy building at the intersection of AI, software engineering, and platform development. You will work hands-on with Python, data pipelines, Kafka/event-driven architecture, APIs, databases, model deployment, MLOps, observability, and production support. You will also have the opportunity to explore and apply emerging technologies such as GenAI, LLMs, RAG, and Agentic AI to solve real business problems at scale.
We are looking for someone with strong software engineering fundamentals, a production-first mindset, and the ability to balance innovation with reliability, scalability, security, and maintainability. If you enjoy solving complex problems, building enterprise-grade AI platforms, and shaping the future of AI-powered experiences, this is a great opportunity to make meaningful impact at Target.
Key Responsibilities
Build production-grade AI/ML applications and services using Python, following software engineering best practices for clean code, testing, documentation, reliability, and maintainability.
Design and develop scalable data and ML pipelines for batch and real-time processing using Kafka, distributed processing frameworks, and workflow orchestration tools.
Implement end-to-end model training, evaluation, deployment, and inference workflows that can scale across large datasets and enterprise workloads.
Build and deploy REST APIs, microservices, and event-driven integrations to expose AI/ML capabilities to downstream applications and business workflows.
Work with SQL and NoSQL databases to store, retrieve, transform, and manage structured and unstructured data for AI/ML use cases.
Support production deployment and lifecycle management through CI/CD, containerization, model versioning, automated validation, and release processes.
Implement observability and reliability mechanisms, including logging, monitoring, alerting, error handling, and root-cause analysis for production AI systems.
Optimize model services for latency, throughput, cost, scalability, and operational performance.
Collaborate with Data Scientists to convert prototypes, notebooks, and experimental models into reliable, maintainable, and scalable production solutions.
Evaluate and integrate GenAI / LLM components, including prompt workflows, RAG pipelines, evaluators, guardrails, and orchestration patterns where applicable.
About You:
Bachelor’s degree in Computer Science or equivalent experience, with 4+ years in software design, development, and algorithmic solutions.
Must-Have Skills:
Proven experience building and deploying end-to-end AI/ML pipelines, including:
Data preparation and feature engineering
Model training and evaluation
Model deployment and inferencing
Production monitoring and lifecycle management
Strong hands-on experience with MLOps practices and tools, including CI/CD for ML, model versioning, automated retraining, and production deployment.
Preferred / Good-to-Have Skills:
Experience building applications using Generative AI (LLMs), including prompt engineering, RAG architectures, evaluation frameworks, and model orchestration.
Exposure to Agentic AI systems, including multi-agent workflows, planning, tool usage, orchestration frameworks, and autonomous decision-making patterns.
Experience implementing LLM observability, evaluation, and guardrails for production GenAI systems.
Experience building reusable AI platforms or shared ML services used across multiple teams.
Experience designing and operating scalable inference systems capable of supporting production workloads.
Good understanding of observability and reliability for ML systems, including monitoring, alerting, performance tracking, debugging, and root-cause analysis.
Strong software engineering fundamentals, including Python development, testing, code reviews, error handling, and production-quality coding practices.
Experience working with cloud-based ML platforms and modern ML frameworks.
Know More About us here:
Life at Target- https://india.target.com/
Benefits- https://india.target.com/life-at-target/workplace/benefits
Culture- https://india.target.com/life-at-target/belonging
