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Data scientist
India - Karnataka - BangalorePosted 2 days ago
Full-timeonsite
Job Description
Experience: 2–6 years
Location: Bangalore
Employment Type: Full-time
Staff Level: T8/T9
Responsibilities:
- Design and develop scalable applications leveraging Generative AI technologies for software process automation and intelligent data retrieval.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines using LLMs and VLMs to enhance chatbot capabilities and contextual understanding.
- Collaborate with cross-functional teams to deploy AI-powered solutions on Azure cloud infrastructure.
- Integrate Python-based backend services with cloud-native tools for seamless deployment and monitoring.
- Continuously evaluate and improve application performance, security, and reliability in production environments.
Required Skillsets:
- GenAI Expertise: Hands-on experience with LLMs (e.g., GPT, LLama), VLMs, and RAG architecture.
- Programming: Strong proficiency in Python, including frameworks like FastAPI, LangChain, or similar. Need solid skills using Pyspark for processing big data (efficient data transformations)
- Cloud & DevOps: Experience deploying and managing applications on Azure, including Azure Functions, App Services, and Azure AI services.
- Database & Retrieval: Familiarity with vector databases (e.g., ChromaDB, Pinecone) and efficient data retrieval techniques.
- Software Engineering: Solid understanding of software development lifecycles, version control (Git), and CI/CD pipelines.
Experience: 2–6 years
LocatioExperience: 2–6 years
Location: Bangalore
Employment Type: Full-time
Staff Level: T8/T9
Responsibilities:
- Design and develop scalable applications leveraging Generative AI technologies for software process automation and intelligent data retrieval.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines using LLMs and VLMs to enhance chatbot capabilities and contextual understanding.
- Collaborate with cross-functional teams to deploy AI-powered solutions on Azure cloud infrastructure.
- Integrate Python-based backend services with cloud-native tools for seamless deployment and monitoring.
- Continuously evaluate and improve application performance, security, and reliability in production environments.
Required Skillsets:
- GenAI Expertise: Hands-on experience with LLMs (e.g., GPT, LLama), VLMs, and RAG architecture.
- Programming: Strong proficiency in Python, including frameworks like FastAPI, LangChain, or similar. Need solid skills using Pyspark for processing big data (efficient data transformations)
- Cloud & DevOps: Experience deploying and managing applications on Azure, including Azure Functions, App Services, and Azure AI services.
- Database & Retrieval: Familiarity with vector databases (e.g., ChromaDB, Pinecone) and efficient data retrieval techniques.
- Software Engineering: Solid understanding of software development lifecycles, version control (Git), and CI/CD pipelines.n: Bangalore
Employment Type: Full-time
Staff Level: T8/T9
Responsibilities:
- Design and develop scalable applications leveraging Generative AI technologies for software process automation and intelligent data retrieval.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines using LLMs and VLMs to enhance chatbot capabilities and contextual understanding.
- Collaborate with cross-functional teams to deploy AI-powered solutions on Azure cloud infrastructure.
- Integrate Python-based backend services with cloud-native tools for seamless deployment and monitoring.
- Continuously evaluate and improve application performance, security, and reliability in production environments.
Required Skillsets:
- GenAI Expertise: Hands-on experience with LLMs (e.g., GPT, LLama), VLMs, and RAG architecture.
- Programming: Strong proficiency in Python, including frameworks like FastAPI, LangChain, or similar. Need solid skills using Pyspark for processing big data (efficient data transformations)
- Cloud & DevOps: Experience deploying and managing applications on Azure, including Azure Functions, App Services, and Azure AI services.
- Database & Retrieval: Familiarity with vector databases (e.g., ChromaDB, Pinecone) and efficient data retrieval techniques.
- Software Engineering: Solid understanding of software development lifecycles, version control (Git), and CI/CD pipelines.