Associate Lead - AI/ML Engineer ( Python, AL/ML)

About the Role
We are looking for a strong AI Engineer / Machine Learning Engineer to build and optimize enterprise search, ranking, recommendation, and AI-powered retrieval solutions across financial-services use cases.
Key Responsibilities
Develop and optimize enterprise search systems, indexing, ranking, and query relevance.
Build AI/ML solutions for search, personalization, recommendations, and retrieval.
Work on taxonomy, ontology, metadata, embeddings, and semantic search.
Build RAG and knowledge-retrieval solutions using vector search and semantic retrieval.
Analyze user behavior and system metrics to improve search accuracy and relevance.
Collaborate with business, engineering, product, and design teams.
Develop and deploy production-grade ML systems with CI/CD, testing, and monitoring.
Drive POCs and emerging AI/ML initiatives.
Requirements
Mandatory Requirements
3+ years of hands-on experience in AI / ML / Data Science / NLP / Deep Learning / GenAI.
Strong Python, SQL, data analysis, feature engineering, and ML model development experience.
Hands-on experience with PyTorch / TensorFlow / Keras / Scikit-learn or equivalent.
Experience in NLP, embeddings, semantic search, recommendations, document understanding, or related AI/ML use cases.
Hands-on experience with LLMs such as GPT, Llama, Mistral, Claude, Gemini, Phi, or similar.
Proven experience with RAG, vector search, embeddings, chunking, indexing, and semantic retrieval.
Strong experience with Git, CI/CD, production environments, and scalable ML systems.
B.Tech/M.Tech from Tier-1 institutes – IITs, NITs, BITS.
Age: Below 28 years.
CTC structure: 75% Fixed + 25% Variable.
Good to Have
MLflow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, MLOps/LLMOps.
Vector Databases, Spark/PySpark, distributed ML pipelines, or real-time ML systems.
Docker, Kubernetes, Azure/AWS/GCP, and cloud-native AI deployments.
Experience in FinTech, Banking, Lending, Fraud/Risk Analytics, AI-first startups, Product, or SaaS companies.

Work arrangement
No