Overview

This is a 3rd party contractual role. Location is Kolkata.

Responsibilities

• Design, develop, evaluate, and deploy Machine Learning models for classification, regression, forecasting, clustering, recommendation systems, anomaly detection, and optimization problems.
• Perform exploratory data analysis (EDA), feature engineering, feature selection, and model tuning.
• Develop robust data preprocessing and feature engineering pipelines.
• Build reusable ML components and production-ready prediction services.
• Monitor model performance and implement continuous improvements and retraining strategies.
• Develop explainable and interpretable ML solutions wherever applicable.
• Design and develop Generative AI applications using Large Language Models (LLMs).
• Build Retrieval Augmented Generation (RAG) systems using Vector Databases.
• Develop intelligent AI assistants, copilots, chatbots, document intelligence, knowledge search, and workflow automation solutions.
• Implement prompt engineering strategies for reliable and accurate AI responses.
• Develop Agentic AI workflows using orchestration frameworks.
• Build document ingestion, indexing, embedding, retrieval, and semantic search pipelines.
• Optimize LLM performance, latency, token utilization, and response quality.
• Develop scalable backend services for ML and GenAI applications.
• Build REST APIs for AI models and services.
• Deploy AI applications using containerized environments.
• Design modular and reusable AI application architectures.
• Integrate AI models with enterprise applications and business workflows.
• Develop logging, monitoring, exception handling, and performance optimization mechanisms.
• Package and deploy ML/AI models into production.
• Build automated inference pipelines.
• Monitor model drift, data drift, and application performance.
• Maintain model versioning and deployment pipelines.
• Troubleshoot production issues and optimize system reliability.
• Develop SQL queries and data extraction pipelines.
• Work with structured and semi-structured datasets.
• Design efficient database interactions for AI applications.
• Build data pipelines supporting AI model training and inference.
• Stay current with advancements in Machine Learning, Deep Learning, Generative AI, LLMs, Agentic AI, and AI infrastructure.
• Evaluate emerging AI frameworks, tools, and libraries.

Qualifications

• Python (Advanced)
• Object-Oriented Programming
• Python Packaging and Virtual Environments
• Git Version Control
• Scikit-learn
• Statsmodels
• NumPy
• Pandas
• Model Evaluation Techniques
• Hyperparameter Tuning
• Feature Engineering
• Time Series Analysis
• Classification
• Regression
• Clustering
• Forecasting
• Ensemble Learning
• Strong hands-on experience with:
• Large Language Models (LLMs)
• Prompt Engineering
• Retrieval Augmented Generation (RAG)
• Embeddings
• Semantic Search
• Document Processing
• AI Agents
• Multi-Agent Workflows
• Context Management
• Function Calling / Tool Use
• Structured Output Generation
• LangChain

Education

• Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Artificial Intelligence, Mathematics, Engineering, or a related discipline.