About the role
Responsibilities:
- Build and deploy ML models for real-world business problems.
- Design and optimise RAG pipelines and retrieval systems.
- Develop LLM-powered agents and workflow automation systems.
- Work closely with founders, product, and engineering teams.
- Translate ambiguous problems into scalable AI solutions.
- Continuously improve model performance, accuracy, and reliability.
Requirements:
- 3-7 years of experience in Machine Learning / Applied AI.
- Strong foundation in Machine Learning, Statistics, and Probability.
- Hands-on experience with Python and ML frameworks
- Experience building RAG systems and LLM-powered applications
- Understanding of agentic workflows, tool calling, and orchestration.
- Strong problem-solving skills and product mindset.
- Ability to move quickly from prototype to production.
- Strong academic background with a B. Tech/M. Tech from a Tier-1 institution and demonstrated excellence in quantitative subjects.
Bonus Points:
- Experience in fintech, wealth tech, or financial services.
- Experience with LangGraph, LlamaIndex, LangChain, CrewAI, or similar frameworks.
- Experience building production-grade AI systems.