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Salary
≈ $16k – $39k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 4+ years exp

First seen by Alion on Sep 24, 2026.

Overview
Company
Impact
Profile match

Job Description :


What you'll work on :

- Building and owning a conversational AI research assistant for retail investors in Indian capital markets, think Claude but specialized for different instruments and macro analysis for non-expert users


- Designing multi-agent agentic pipelines with tool-calling, memory management, and multi-turn conversational flows that handle real, messy, incomplete queries from retail users (not just clean, structured prompts from analysts)


- RAG pipeline architecture : source curation, chunking strategy, embedding quality, retrieval tuning, reranking, and citation-grounded responses that retail users can trust


- Integrating real-time financial data sources (NSE/BSE feeds, Screener, Tickertape, news APIs, company filings) as live tool-callable data layers, not just static retrieval


- Building the guardrails and evaluation layer : domain scoping, hallucination mitigation, confidence scoring, and monitoring to ensure the system stays accurate and within bounds over time


- Fine-tuning or adapting LLMs where retrieval alone isn't sufficient


- Building ML models for user behaviour, personalization, and financial insights that feed into the conversational layer


Expectations :


- Understanding of large language models (LLMs) like LLAMA, Anthropic Claude 3, or Sonnet.


- Familiarity with cloud platforms for data science like AWS Bedrock and GCP Vertex AI


- Strong proficiency in Python and data science libraries (scikit-learn, TensorFlow, PyTorch).


- Solid understanding of statistical methods, machine learning algorithms, and wealth tech applications.


- Experience in data wrangling, visualization, and analysis.


- Collaborative mindset and ability to thrive in a fast-paced startup environment.


Bonus points :


- Experience in capital market usecases


- Familiarity with recommender systems and personalization techniques.


- Experience building and deploying production models.


- Data science project portfolio or contributions to open-source libraries.


- Experience with embedding models and retrieval quality improvement


- Worked at an AI-first startup in any domain

Skills

Data Science, Data Scientist, Conversational AI, LLM, Machine Learning, Python, Tensorflow

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