About the role
Senior data scientist
Key Responsibilities
Design, build, and deploy production-grade AI and Machine Learning
solutions.
Develop and optimize LLM-powered applications, including RAG,
GraphRAG, Agentic AI, and multimodal systems.
Fine-tune and customize Large Language Models using techniques such as
LoRA, PEFT, and transfer learning.
Build intelligent chatbot, search, recommendation, and knowledge retrieval
systems.
Design and optimize prompt engineering frameworks for business use cases.
Develop scalable AI pipelines, model-serving frameworks, and API-based AI
services.
Work with structured and unstructured data to build predictive and generative
AI solutions.
Collaborate with Product, Engineering, and Business teams to translate
business problems into AI-driven solutions.
Evaluate emerging AI technologies, models, frameworks, and tools and
recommend their applicability to products.
Ensure deployed models are scalable, reliable, secure, and production-ready.
Core Technical Skills
Generative AI (Mandatory)
Large Language Models (LLMs)
RAG (Retrieval-Augmented Generation)
GraphRAG
Prompt Engineering
AI Agents and Agentic Workflows
LLM Fine-Tuning (LoRA, PEFT)
Embeddings & Vector Search
Multimodal AI Applications
Frameworks & Tools (Mandatory)
Python
LangChain
LangGraph
Neo4j
Graph Databases
Vector Databases (Pinecone, ChromaDB, Weaviate, PgVector or equivalent)
Agentic AI (Preferred)
MCP (Model Context Protocol)
Google ADK
AutoGen
CrewAI
Semantic Kernel
Multi-Agent Architectures
Machine Learning (Mandatory)
Strong understanding of:
Classification Models
Regression Models
This page is fully interactive when JavaScript is enabled. Please enable JavaScript to apply or browse related roles.
