Role Overview

We are looking for a highly analytical and hands-on Data Scientist with strong experience in Machine Learning, Large Language Models (LLMs), Generative AI, Agentic AI, and AI model deployment.

The ideal candidate will be responsible for developing and deploying data science solutions, applying advanced machine learning techniques, and leveraging emerging AI technologies to solve complex business problems.

Key Responsibilities

- Develop, train, validate, and optimize Machine Learning models for business use cases.
- Perform exploratory data analysis, feature engineering, data preprocessing, and statistical analysis.
- Apply appropriate machine learning algorithms and evaluate model performance using relevant metrics.
- Work hands-on with Large Language Models (LLMs), Generative AI, and Agentic AI use cases.
- Develop and evaluate LLM-based and Generative AI solutions for real-world business problems.
- Build RAG (Retrieval-Augmented Generation) solutions using embeddings, vector databases, and semantic search.
- Design and implement AI Agent / Agentic AI workflows, including tool calling and multi-step reasoning workflows.
- Perform prompt engineering, model evaluation, experimentation, and optimization.
- Work with structured and unstructured datasets to derive meaningful insights and build predictive solutions.
- Deploy and productionize Machine Learning and AI models.
- Collaborate with engineering teams to integrate models into applications and enterprise platforms.
- Monitor model performance and continuously improve accuracy, reliability, and scalability.




- Communicate analytical findings, model results, and recommendations effectively to technical and business stakeholders.
- Stay updated with emerging developments in Machine Learning, GenAI, LLMs, and Agentic AI.

Mandatory Skills
- Strong analytical and problem-solving skills
- Strong hands-on experience in Data Science and Machine Learning
- Experience developing, evaluating, and optimizing Machine Learning models
- Solid programming skills in Python
- Strong knowledge of statistics, probability, data preprocessing, and feature engineering
- Hands-on experience with LLMs and Generative AI
- Practical experience with Agentic AI / AI Agents
- Experience with RAG, embeddings, vector databases, or semantic search
- Experience with LLM APIs / foundation models
- Experience with AI/ML model deployment and productionization
- Experience with ML libraries/frameworks such as Scikit-learn, PyTorch, or TensorFlow
- Strong SQL skills and experience working with large datasets
- Experience with model evaluation, validation, and performance optimization

Preferred Skills
- LangChain, LangGraph, LlamaIndex or similar GenAI frameworks
- Azure OpenAI, AWS Bedrock, Google Vertex AI or similar platforms
- Vector databases such as FAISS, Pinecone, Weaviate, Milvus, or Azure AI Search
- MLflow or other MLOps platforms
- Docker and Kubernetes
- Git and CI/CD
- Experience with NLP, NLP transformers, or deep learning
- Experience with multi-agent architectures
- Knowledge of Responsible AI, model security, and AI governance

📌 Data Scientist (Chennai)
🏢 AlgoLeap Technologies
📍 Chennai