The Role
Build and deploy LLM systems for production banking use, evaluate AI with offline and live tests, monitor models, and collaborate with Product, Risk, and Compliance; hands-on work with Python, vLLM, prompt optimization, and fine-tuning.
Summary Generated by Built In
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
Skills Required
- Bachelor's or Master's in a quantitative field (Statistics, Computer Science, Math, Engineering, Physics)
- Strong Python fundamentals
- Experience building something with LLMs (thesis, internship, side project, or hackathon) and able to explain it simply
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The Company
What We Do
PT Bank OCBC NISP Tbk is a leading financial institution in Indonesia that provides a wide array of banking products and services to corporate, SME, and individual customers. Operating through business, consumer, and global markets segments, it offers savings, loans, credit cards, mutual funds, and insurance products. The company is a subsidiary of OCBC Overseas Investments Pte. Ltd. and is one of Indonesia's top ten banks.
