Data Scientist - Gen AI Python LLM

Job Details:

Experience - 6 to 8 yrs

Mandatory Skills - Gen AI, Data Science, LLM, Python.

Location - Mumbai, Pune, Bangalore, Chennai, Hyderabad and Kolkata location.

Notice - Immediate to 30 days

Job Description:

• 5 to 8 years of experience in GenAI Python LLM
• 5 years of experience programming in Python
• Knowledge of Python libraries like Pandas ScikitLearn Numpy NLTK is required
• 5 years of experience with Natural Language Processing NLP and Large Language Models LLM
• 3 years of experience building and maintaining scalable API solutions
• Experience working with Sentiment Analysis NameEntity Recognition RAG technologies and LLM frameworks Langchain Claude and LLamaIndex LLM model registries Hugging Face LLM APIs embedding models knowledge graph and vector databases FAISS Milvus OpenSearch Pinecone etc
• Experience building scalable data models and performing complex relational databases queries using SQL Oracle MySQL PostGres etc
• Prefer experience designing knowledge graphs to represent domain knowledge in Neptune or Gremlin and using Graph RAG to retrieve data
• Experience with machine learning libraries and services like Azure Cognitive Services PyTorch or Azure Machine Learning
• Experience integrating Gen AI solution on cloud platform eg AWS Azure Google Cloud
• Programming and Data Processing
• Hands on experience with Python for data processing tasks
• Experience with CI tools such as Jenkins
• Proficient with Git version control systems
• Familiar with issue tracking tools like JIRA
• Agile Development - Familiar with Agile development methodologies
• Azure Cloud Platform - Working experience on the Azure cloud platform
• Azure Data Pipeline - Knowledgeable in building data pipelines on Azure using services like blob storage Azure functions Event Hub etc

Generative AI Experience

1) Retrieval Augmented Generation RAG

Must have Implemented RAG techniques to enhance data retrieval and improve the relevance of generated content

Integrated RAG models with existing data pipelines to optimize information retrieval processes

2) Vector Databases

Utilizing vector databases for efficient storage and retrieval of highdimensional data

Knowledge on vector search algorithms to enhance the performance of AIdriven applications

3) Large Language Models LLMs

Experience with deploying and finetuning large language models for various NLP tasks

Integrated LLMs into data processing workflows to automate and enhance data analysis

4) LangChain

Knowledge on LangChains for building and managing complex data workflows

Experience in scalable data pipelines using LangChain to streamline data processing and integration tasks

5) Efficiency Improvements

Should have implementation experience to reduce data processing times by optimizing ETL workflows and leveraging cloudnative solutions