The Core Responsibilities For The Job Include The Following

AI and LLM Engineering:

Design and develop LLM-powered features, including RAG (Retrieval-Augmented Generation) pipelines and prompt engineering.
Build and evaluate agentic AI systems using frameworks.
Integrate vector databases for semantic search and knowledge retrieval.
Explore self-hosted LLM deployments using Ollama, vLLM, or similar frameworks.

Machine Learning And Modeling

Build, train, and evaluate ML models for credit risk, fraud detection, anomaly detection, and customer segmentation.
Perform feature engineering, hyperparameter tuning, model selection, and error analysis.
Apply ensemble methods (boosting, bagging, stacking) to improve model robustness.
Conduct A/B testing, multivariate experiments, and statistical analysis to validate model performance.

Cloud And Production

Build and maintain scalable ML pipelines and data workflows on cloud infrastructure.
Collaborate with data engineers to integrate models into production systems using MLOps best practices.
Write clean,



production-level Python code and contribute to shared AI tooling and libraries.

Requirements

1-5 years of industry or project experience in AI/ML engineering (internships and academic projects strongly count).
Bachelor's OR master's degree in statistics, computer science, engineering, mathematics, or a related technical field.

AI And LLM Skills (Must Have)

Hands-on experience or solid project exposure to LLM prompt engineering and RAG pipelines.
Familiarity with Hugging Face Transformers, OpenAI API, or equivalent LLM frameworks.
Understanding of vector embeddings, semantic search, and knowledge retrieval concepts.
Awareness of GenAI and Agentic AI methodologies and their practical applications.

Programming / Cloud / Data Skills (Must Have)

Strong Python programming skills and clean, maintainable, production-ready code.
Proficient in ML libraries: scikit-learn, TensorFlow or PyTorch, XGBoost, pandas, and NumPy.
Solid

📌 AI / LLM Engineer (Bengaluru)
🏢 Kaleidofin Private
📍 Bengaluru