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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