Data Scientist – AI/ML & Agentic Systems

Location: Kolkata (On-site)
Experience: 4-5 Years
Education: Master’s degree in computer science /engineering/ data science
Employment Type: Full-Time

Role Overview

We are seeking a highly skilled Data Scientist with expertise in Large Language Models (LLM), Machine Learning, Generative AI, and Agentic AI frameworks to design, build, and deploy intelligent AI solutions, intelligent AI agents and scalable ML systems that integrate with enterprise application.

The ideal candidate will combine strong fundamentals in ML modeling with hands-on experience in LLM integration, RAG pipelines, AI agents, and production-grade ML deployment.

Additionally, S/HE should be a team player with strong communication skill and good command of English.

Key Responsibilities

• Build, train, and deploy advanced ML and AI models (supervised, unsupervised, deep learning)
• Design and implement LLM-powered AI agents and multi-agent workflows
• Develop and optimize Retrieval-Augmented Generation (RAG) pipelines
• Implement end-to-end ML lifecycle: data ingestion, feature engineering, training, deployment, monitoring
• Fine-tune models and optimize prompts for performance and cost
• Deploy production-grade AI systems using Docker, Kubernetes, and cloud platforms
• Monitor models for drift, bias, hallucinations, and performance degradation
• Collaborate with product and engineering teams to translate business problems into AI-driven solutions

Core ML & AI Expertise (Must have)

Machine Learning

• Regression, Classification (Logistic, Random Forest, XGBoost, LightGBM)
• Clustering (K-Means, DBSCAN)
• Time Series (ARIMA, Prophet, LSTM)
• Anomaly Detection (Isolation Forest, One-Class SVM)
• Recommender Systems

Deep Learning & NLP

• CNNs, RNNs, LSTM, Transformers
• BERT and Transformer-based architectures
• Embeddings and semantic search

Generative AI & Agentic Systems

• LLM API integration (OpenAI, Anthropic, AWS Bedrock)
• Prompt engineering (few-shot, chain-of-thought, structured prompting)
• LLM fine-tuning and evaluation
• Agent frameworks: LangChain, LlamaIndex, AutoGen, CrewAI
• Tool calling & function execution frameworks
• Vector databases (Pinecone, Weaviate, FAISS)
• Hybrid search (semantic + keyword)

Technical Stack

• Languages: Python (Primary), SQL
• ML Frameworks: Scikit-learn, TensorFlow, PyTorch
• API Frameworks: FastAPI / Flask
• MLOps: MLflow, CI/CD pipelines, model monitoring
• Cloud: AWS (Bedrock, SageMaker), Azure OpenAI, GCP AI
• Infrastructure: Docker, Kubernetes

Required Qualifications

• 4-5 years of demonstrated experience in Data Science / ML
• 1–2+ years of hands-on experience with LLM-based systems
• Strong background in statistics, probability, and model evaluation
• Experience deploying AI systems in production environments

Preferred Skills (Good to have)

• Experience with open-source LLMs (Llama, Mistral)
• Knowledge of RLHF / alignment techniques
• Experience building AI copilots or enterprise automation agents
• Exposure to Responsible AI, governance, and security

** Candidates who meet the above criteria and are available to join immediately will be given preference.