AI / LLM Engineer

Kaleidofin Private Limited

Required skills

Website: kaleidofin.com
Job details:
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 strong 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 SQL skills for data querying, transformation, and mining structured datasets.
Experience normalizing and preprocessing data for consistency, quality, and model readiness.
Working knowledge of at least one major cloud platform: AWS, GCP, or Azure.
Understanding of cloud storage, compute, and containerization basics (Docker, Kubernetes).
Exposure to big data tools such as Spark or Hadoop (MapReduce, Hive, Pig) is a plus.

Machine Learning Algorithms (Good To Have)

Clear understanding, coding, implementation, error analysis, and model tuning across:
Supervised Learning: Linear Regression, Logistic Regression, SVM, Decision Trees, Random Forest, and XGBoost.
Neural Networks: Shallow neural networks and familiarity with deep learning architectures.
Unsupervised Learning: Clustering (K-Means, DBSCAN), Recommender Systems.
Time Series and Anomaly Detection: ARIMA, Isolation Forest, statistical anomaly methods.
Strong command of model selection, cross-validation, feature selection, and ensemble methods (boosting, bagging, stacking).
Ability to perform hyperparameter tuning using Grid Search, Random Search, or Bayesian optimization.

Nice To Have

Experience in fintech, credit scoring, risk analytics, or financial inclusion domains.
Contributions to open-source ML/AI projects or a strong personal project portfolio on GitHub.
Familiarity with MCP (Model Context Protocol) or building AI tool integrations.
Experience with MLflow, Weights & Biases, or other experiment tracking tools.

Soft Skills

Genuine curiosity about AI/ML and eagerness to learn in a fast-moving field.
Strong problem-solving mindset able to break down complex challenges into actionable steps.
Clear communication skills to present model results and insights to non-technical stakeholders.
Collaborative team player who thrives in a cross-functional, mission-driven environment.

This job was posted by Poornima B from Kaleidofin. Click on Apply to know more.

This page is fully interactive when JavaScript is enabled. Please enable JavaScript to apply or browse related roles.