Data Scientist (Conversational AI)

Uberlife Consulting; Bengaluru; On-site; INR 900,000 - 1,200,000; Full time

Job summary

Uberlife Consulting in Bengaluru is seeking a GenAI-focused engineer to build a conversational research assistant for retail investors in the Indian capital markets. You will design multi-agent AI pipelines, integrate real-time market data via APIs, and implement safety rails with evaluation and confidence scoring.

The role requires strong Python and data science skills and hands-on experience with LLMs, RAG, and model deployment.

Qualifications

• Strong Python & Data Science expertise with PyTorch/TensorFlow/scikit-learn
• Hands-on experience with LLMs, RAG, embeddings and/or agentic AI
• Exposure to AWS Bedrock / GCP Vertex AI
• Strong ML, statistics, data analysis & model deployment experience
• Experience in capital markets / fintech or an AI-first startup would be a strong plus

Responsibilities

• Build multi-agentic AI pipelines with tool calling, memory & multi-turn conversations
• Architect RAG pipelines, retrieval, reranking & citation-grounded responses
• Integrate real-time market data, news & company filings through APIs/tools
• Build guardrails, evaluation frameworks, hallucination mitigation & confidence scoring
• Fine-tune/adapt LLMs where required and build ML models for personalization & financial insights

Skills

Python & DS

LLMs & RAG

ML platforms

ML & analytics

Capital markets

Tools

AWS Bedrock

GCP Vertex AI

PyTorch

TensorFlow

scikit-learn

Embeddings

Job description

Opportunity to work on a GenAI-powered conversational research assistant for retail investors, focused on Indian capital markets.

Key areas of work:

• Build multi-agentic AI pipelines with tool calling, memory & multi-turn conversations
• Architect RAG pipelines, retrieval, reranking & citation-grounded responses
• Integrate real-time market data, news & company filings through APIs/tools
• Build guardrails, evaluation frameworks, hallucination mitigation & confidence scoring
• Fine-tune/adapt LLMs where required and build ML models for personalization & financial insights

What were looking for:

• Strong Python & Data Science expertise with PyTorch/TensorFlow/scikit-learn
• Hands-on experience with LLMs, RAG, embeddings and/or agentic AI
• Exposure to AWS Bedrock / GCP Vertex AI
• Strong ML, statistics, data analysis & model deployment experience
• Experience in capital markets / fintech or an AI-first startup would be a strong plus