What you'll do:
- Build and ship LLM systems and workflows to production, where real bankers and customers use them
- Learn to evaluate AI properly: offline evals, A/B tests, live monitoring
- Work hands-on with Python, vLLM, prompt optimization, and fine-tuning
- Work alongside experienced teams in Product, Risk, and Compliance to apply data science techniques to real-world banking scenarios, including credit risk and regulatory compliance.
We’re looking for curious and eager-to-learn candidates who are:
- Fresh graduate (Bachelor's or Master's) in a quantitative field: Statistics, Computer Science, Math, Engineering, Physics
- Strong Python fundamentals
- Have experience on building something with LLMs (through Thesis, internship, side project, or hackathon) and can explain the concept and its objective in a simple way
Bonus points (not required):
- Exposure to vLLM, LoRA/QLoRA fine-tuning, or prompt optimization frameworks like GEPA
- Interest in financial data and regulation
