Must have • 3–4 years of experience building AI/ML applications with strong Python and software engineering skills. • Strong proficiency in Python. • Hands-on experience with: o Understanding of AI system design, evaluation, monitoring, and performance optimization. o Experience developing, deploying, and maintaining production AI applications. o Strong software engineering fundamentals, including clean code, modular design, debugging, and testing. o RAG architectures • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. • Good understanding of NLP concepts . • Familiarity with API development and integration. • Ability to work independently as well as in cooperative team environments. Good to have • Experience with vector databases such as Pinecone, Weaviate, FAISS, ChromaDB. • Knowledge of cloud platforms such as AWS, Azure, or GCP. • Experience with Docker, and deployment pipelines. • Exposure to fintech products, platforms, or domain-specific use cases.



Roles & Responsibilities • Design scalable, reliable AI systems with a focus on production readiness, maintainability, and performance. • Perform root cause analysis and debugging of AI pipelines to improve accuracy, consistency, and reliability. • Develop automated evaluation, validation, and testing strategies for AI applications. • Design reliable LLM workflows using structured outputs, validation, retrieval, and business rules. • Create and maintain RAG pipelines and AI agent frameworks. • Perform data analysis, model evaluation, and performance optimization. • Develop APIs and integrate AI solutions into existing products and platforms. • Collaborate with cross-functional teams including engineering, and business stakeholders to define AI use cases and deliver solutions. • Monitor, troubleshoot, and continuously improve deployed AI systems.

📌 BI Data Modeler (Gurugram)
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📍 Gurugram