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)
- Solid Python programming skills and clean, maintainable, production-ready code.
- Proficient in ML libraries: scikit-learn, TensorFlow or PyTorch, XG

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