Job highlights

- Expertise in Machine Learning, Deep Learning, Generative AI, LLMs, and MLOps tools like MLflow and Kubeflow

- Design, develop, and deploy AI/ML models; build scalable pipelines; fine-tune foundation models; integrate AI solutions; monitor model performance

Key Responsibilities

- Design, develop, and deploy Machine Learning and AI models for business applications.

- Build scalable AI/ML pipelines for training, testing, deployment, and monitoring.

- Perform data collection, preprocessing, feature engineering, and model optimization.

- Develop predictive, classification, recommendation, and forecasting models.

- Implement Deep Learning models using industry-standard frameworks.

- Build Generative AI solutions leveraging Large Language Models (LLMs).

- Fine-tune foundation models and optimize inference performance.

- Collaborate with business teams to translate requirements into AI-driven solutions.

- Develop APIs and integrate AI models into enterprise applications.

- Establish MLOps best practices for model lifecycle management.

- Monitor model performance, drift, and retraining requirements.

- Create technical documentation, architecture diagrams, and deployment guides.





- Stay updated with emerging AI technologies and industry trends.

Required Skills

Artificial Intelligence & Machine Learning

- Machine Learning Algorithms

- Supervised & Unsupervised Learning

- Reinforcement Learning

- Deep Learning

- Generative AI

- Natural Language Processing (NLP)

- Computer Vision

- Recommendation Systems

- Time Series Forecasting

Programming

- Python

- SQL

- PySpark

- R (Preferred)

AI/ML Frameworks

- TensorFlow

- PyTorch

- Keras

- Scikit-learn

- XGBoost

- LightGBM

Generative AI

- LLMs

- Prompt Engineering

- RAG (Retrieval-Augmented Generation)

- Vector Databases

- LangChain

- Semantic Search

- AI Agents

Data Engineering

- ETL/ELT Pipelines

- Data Warehousing

- Data Lakes

- Feature Engineering

- Data Validation

MLOps & Deployment

- MLflow

- Kubeflow

- Docker

- Kubernetes

- CI/CD Pipelines

- Model Monitoring

- A/B Testing

Cloud Platforms

- AWS SageMaker

- Azure AI Services

- Microsoft Fabric

- Google Vertex AI

- Databricks

Databases

- PostgreSQL

- MySQL

- MongoDB

- Snowflake

📌 AI/ML Engineer - S (Kolkata)
🏢 Tata Consultancy Services
📍 Kolkata