Experience:

• 4+ years of experience in software engineering, AI engineering, machine learning engineering, data engineering, MLOps, or production ML systems

Qualification:

• Bachelor's degree in Computer Science, Engineering, Data Science, Machine Learning, Mathematics, Statistics, or a related technical field, or equivalent practical experience

Role Focus:

• Build production-grade AI/ML applications, services, and platforms using Python and modern engineering practices
• Design and develop scalable data and ML pipelines for batch, streaming, and near-real-time processing
• Implement end-to-end model training, evaluation, deployment, inference, monitoring, and lifecycle management workflows
• Partner with Data Scientists to convert prototypes, notebooks, statistical models, ML models, GenAI workflows, and optimization algorithms into reliable, reusable, and production-ready systems
• Build and deploy REST APIs, microservices, model-serving endpoints, batch scoring jobs, and event-driven integrations

Additional responsibilities:

• Support production deployment and release management through CI/CD, containerization, automated testing, model versioning, automated validation, release controls, rollback strategies, and environment management
• Implement observability and reliability mechanisms, including logging, metrics, traces, dashboards, alerting, error handling, incident response, and root-cause analysis for production AI systems
• Optimize AI/ML services for latency, throughput, cost, scalability, reliability, and operational performance
• Troubleshoot production issues across data pipelines, model services, APIs, optimization workflows, and downstream integrations

Nice to have:

• Experience building applications using Generative AI and LLMs, including prompt engineering, RAG architectures, embeddings, vector databases, evaluation frameworks, and model orchestration
• Exposure to agentic AI systems, including multi-agent workflows, planning, tool usage, orchestration frameworks, and autonomous or semi-autonomous decision-making patterns
• Experience implementing LLM observability, evaluation, guardrails, safety controls, and responsible AI practices for production GenAI systems
• Experience with promotion optimization, personalization, recommender systems, marketing technology, retail media, customer targeting, pricing, or offer decisioning

More skills:

distributed data pipelines, event-driven architectures, databases, model deployment, ML workflow orchestration, observability, production support, model evaluation frameworks, intelligent workflow automation

Other:

• Life at Target: (know more about the company culture)
• Target Corporation India Pvt. Ltd. is a Fortune 50 company with more than 400,000 team members worldwide
• The company operates in an inclusive learning environment that values people and delivers world-class outcomes