Senior Data Scientist – AI/ML, GenAI & LLM Solutions

Skills:
Deep Learning, GenAI & LLM Solutions, Machine Learning & Advanced Analytics, NLP & Transformers, MLOps & Deployment, Cloud & Data Engineering

Department: Data Science / AI Engineering
Employment Type: Full Time
Work Mode: Onsite / Hybrid
Notice Period: Immediate to 30 Days

About the Role

We are looking for a highly experienced Senior Data Scientist with deep expertise in Machine Learning, Generative AI, and Large Language Models (LLMs) to design and deploy production-grade AI systems.

This role will focus on building scalable AI solutions such as LLM-powered applications, recommendation engines, forecasting models, and intelligent automation systems. You will collaborate with cross-functional teams to translate complex business problems into impactful AI-driven solutions and contribute to the overall AI strategy.

Key Responsibilities

GenAI & LLM Solutions

• Design and develop LLM-based applications using transformer models (GPT, LLaMA, Mistral, etc.)
• Build and deploy Retrieval-Augmented Generation (RAG) pipelines with vector databases
• Develop multi-agent AI systems using orchestration frameworks (LangChain / LangGraph)
• Implement advanced prompt engineering and optimization strategies
• Ensure model safety, guardrails, and output reliability for enterprise-grade deployments

Machine Learning & Advanced Analytics

• Develop ML models for:
  • Forecasting
  • Recommendation systems
  • Fraud detection
  • Customer analytics and churn prediction
• Perform feature engineering, model tuning, and performance optimization
• Conduct statistical analysis, A/B testing, and hypothesis validation
• Work with structured and unstructured large-scale datasets

NLP & Deep Learning

• Build NLP pipelines using transformers, embeddings, and language models
• Implement use cases like:
  • Sentiment analysis
  • Topic modeling
  • Document intelligence
• Develop deep learning models (CNN, RNN, LSTM) using modern frameworks

MLOps & Deployment

• Manage end-to-end ML lifecycle (training → validation → deployment → monitoring)
• Implement CI/CD pipelines for ML and GenAI systems
• Deploy models via APIs and scalable endpoints
• Ensure performance monitoring, observability, and continuous improvement

Cloud & Data Engineering

• Work with cloud platforms (AWS / Azure / GCP) for scalable deployments
• Build data pipelines and data processing systems using SQL, PySpark, etc.
• Develop APIs and dashboards using frameworks like Flask / FastAPI / Streamlit
• Handle large-scale distributed datasets and optimize data workflows

Required Skills & Experience

• Experience: 6–12 years in Data Science, AI/ML, and GenAI
• Strong programming skills in Python, SQL
• Expertise in ML frameworks: scikit-learn, XGBoost, TensorFlow, PyTorch
• Hands-on experience with:
  • LLMs, GenAI frameworks, and RAG architectures
  • NLP and transformer-based models
• Experience with MLOps tools, model deployment, and CI/CD pipelines
• Strong understanding of statistics, data modeling, and experimentation
• Experience working with cloud platforms and distributed systems

What We Look For

• Strong analytical and problem-solving mindset
• Proven experience in deploying scalable, production-grade AI systems
• Ability to translate business requirements into data-driven solutions
• Experience working in fast-paced, high-growth environments
• Strong collaboration and stakeholder management skills
• Leadership ability, including mentoring junior team members

Preferred Qualifications

• Bachelor’s/Master’s degree in Computer Science, Data Science, AI, or related field
• Certifications in Machine Learning, Deep Learning, or Generative AI
• Experience building enterprise-grade AI/LLM applications
• Exposure to multi-modal AI, agentic systems, or GenAI platforms

Why This Role is High Impact

• Work on cutting-edge GenAI and LLM-driven systems
• Opportunity to build scalable, real-world AI products
• Direct influence on product innovation and business outcomes
• High ownership with strong growth and leadership opportunities

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