Data Scientist + AI Engineer

Experience: 8+Year

Budget: 1.1L-1.6L

JD:

Job Overview

We are seeking a highly skilled and experienced Data Scientist + AI Engineer to join our growing AI team. The ideal candidate will have extensive experience in data science, machine learning, generative AI, and large language models (LLMs). You will be responsible for designing, developing, deploying, and optimizing AI-powered applications and intelligent automation solutions that solve complex business challenges.

This role requires expertise in building scalable machine learning systems, implementing agentic AI solutions, developing multi-agent architectures, and deploying production-ready AI applications using AWS cloud services.

Key Responsibilities

• Design, develop, and deploy machine learning and AI models for real-world business applications.
• Analyze structured and unstructured datasets to derive actionable insights and support strategic decision-making.
• Develop and implement Large Language Model (LLM) applications using modern AI frameworks.
• Build Agentic AI and multi-agent systems using LangChain, LangGraph, MCP, and related technologies.
• Fine-tune, evaluate, and optimize foundation models and LLMs.
• Develop Retrieval-Augmented Generation (RAG) pipelines and intelligent AI assistants.
• Build scalable MLOps pipelines for model training, deployment, monitoring, and versioning.
• Collaborate with cross-functional teams including software engineers, product managers, and business stakeholders.
• Design cloud-native AI solutions using AWS services.
• Implement data preprocessing, feature engineering, model evaluation, and performance optimization techniques.
• Monitor model performance and continuously improve production AI systems.
• Stay updated with the latest advancements in Artificial Intelligence, Machine Learning, and Generative AI.

Required Skills & Qualifications

Experience

• 8+ years of professional experience in Data Science, Machine Learning, or AI Engineering.
• Proven experience delivering AI solutions in production environments.

Programming

• Strong proficiency in Python.
• Experience with SQL for data analysis and manipulation.

Mathematics & Statistics

• Strong understanding of:
  • Linear Algebra
  • Advanced Calculus
  • Probability
  • Descriptive Statistics
  • Inferential Statistics

Machine Learning

• Regression
• Classification
• Clustering
• Dimensionality Reduction
• Feature Engineering
• Model Evaluation
• Hyperparameter Tuning
• Time Series Forecasting (preferred)

Deep Learning

• Neural Networks
• CNNs
• RNNs/LSTMs
• Transformer Architectures

Generative AI & LLMs

• Hands-on experience with:
  • Large Language Models (LLMs)
  • Prompt Engineering
  • Agentic AI
  • Multi-Agent Systems
  • Model Context Protocol (MCP)
  • LangChain
  • LangGraph
  • Retrieval-Augmented Generation (RAG)
  • Vector Databases
  • AI Agent Orchestration

MLOps

• Model training and deployment
• CI/CD for Machine Learning
• Model monitoring
• Experiment tracking
• Model versioning
• Pipeline automation

AWS Cloud

Hands-on experience with:

• IAM
• Amazon S3
• AWS Lambda
• API Gateway
• DynamoDB
• Amazon SageMaker
• Amazon OpenSearch
• CloudWatch
• Step Functions (preferred)

Frameworks & Tools

• Scikit-learn
• Pandas
• NumPy
• Jupyter Notebook
• TensorFlow
• PyTorch
• Hugging Face Transformers
• MLflow (preferred)
• Docker
• Git

Preferred Qualifications

• Master’s or PhD in Computer Science, Artificial Intelligence, Data Science, Mathematics, or a related field.
• Experience building scalable AI products deployed in production.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Knowledge of distributed computing frameworks such as Spark.
• Experience working in Agile development environments.
• Familiarity with LLM evaluation frameworks and AI safety best practices.

Preferred Skills

• Retrieval-Augmented Generation (RAG)
• Knowledge Graphs
• Semantic Search
• Vector Databases (Pinecone, FAISS, Weaviate, ChromaDB)
• Prompt Engineering
• AI Workflow Automation
• Autonomous AI Systems
• Explainable AI (XAI)

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent communication and stakeholder management skills.
• Ability to work independently as well as collaboratively in cross-functional teams.
• Strong ownership mindset and attention to detail.
• Passion for learning and adopting emerging AI technologies.

What We Offer

• Opportunity to work on cutting-edge AI and Generative AI projects.
• Exposure to enterprise-scale AI platforms and cloud-native architectures.
• Collaborative and innovative work environment.
• Flexible work arrangements.
• Competitive compensation and career growth opportunities.