About the Role :

We are looking for a highly skilled AI/ML Engineer to build intelligent search, retrieval, ranking, recommendation, and Generative AI solutions at scale. You will work on cutting-edge NLP, semantic search, LLM, and RAG systems that power business-critical experiences across financial products.

Responsibilities :

- Build and optimize enterprise-scale search, ranking, and recommendation systems.

- Develop AI/ML models for semantic search, personalization, and information retrieval.

- Design and implement indexing, embeddings, retrieval, and relevance optimization solutions.

- Build production-grade RAG applications leveraging LLMs and vector databases.

- Create taxonomy, ontology, and metadata frameworks to enhance search quality.

- Analyze user behavior and system performance to continuously improve search outcomes.

- Collaborate with Product, Engineering, Design, and Business teams to deliver AI-powered solutions.

- Develop scalable ML pipelines and deploy models in production environments.

- Drive experimentation, proof-of-concepts, and innovation initiatives in AI and GenAI.

- Follow engineering best practices across testing, CI/CD, monitoring, and deployment.

Requirements :

- 5+ years of hands-on experience in Data Science, Machine Learning, Applied AI, NLP, Deep Learning, or Generative AI.

- Strong proficiency in Python, SQL, feature engineering, model development, and production ML systems.

- Experience with PyTorch, TensorFlow, Keras, Scikit-learn, or similar ML frameworks.

- Hands-on experience in NLP, embeddings, semantic search, document understanding, recommendation systems, or related AI applications.

- Experience working with Large Language Models (GPT, Llama, Claude, Gemini, Mistral, Phi, etc.).

- Strong expertise in RAG, vector search, knowledge retrieval, chunking, indexing, and semantic retrieval architectures.

- Experience with Git, CI/CD pipelines, scalable deployments, and production environments.

- B.Tech/M.Tech from Tier-1 institutes (IITs, NITs, BITS).

- Age below 30 years.

Preferred:

- Experience with MLFlow, Kubeflow, Airflow, Prefect, Feature Stores, Model Registry, MLOps, or LLMOps.

- Exposure to Vector Databases, Spark, PySpark, large-scale data processing, and distributed ML systems.

- Experience with Docker, Kubernetes, AWS, Azure, GCP, and cloud-native AI deployments.

- Background in AI-first startups, Fintech, Banking, Lending, Risk Analytics, Fraud Analytics, SaaS, or Product organizations.

Compensation :

- CTC Structure : 75% Fixed + 25% Variable.

Why Join Us :

Join one of India's leading financial services organizations and build next-generation AI products that impact millions of users. Work on challenging problems in Search, GenAI, LLMs, and Intelligent Automation while collaborating with some of the brightest minds in technology and finance.