LLM Fine-Tuning & Deployment Engineer

DOKU, PT NUSA SATU INTI ARTHA; Jakarta Pusat; On-site; IDR 40,000,000 - 70,000,000; Full time

Job summary

DOKU, PT NUSA SATU INTI ARTHA is seeking an AI Expert to fine-tune, deploy, and optimize LLM-based chatbot systems. You will build scalable pipelines, implement observability, and balance latency, cost, and accuracy across multilingual financial use cases.

The role requires 3–5 years of AI/ML experience, strong knowledge of LangChain, Unsloth, and popular frameworks, and the ability to translate business needs into AI capabilities. Onsite collaboration with product and data teams is expected.

Qualifications

• Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or related field.
• 3–5 years in AI/ML with proven experience fine-tuning and deploying LLM-based chatbot systems.
• Strong experience with LLM frameworks and deployment pipelines.

Responsibilities

• Fine-tune and optimize LLMs for chatbot applications and NLP tasks.
• Build and manage deployment pipelines using LangChain, Unsloth, or equivalent.
• Implement LLM observability tools to monitor model behavior and health.
• Optimize chatbot models for latency, token usage, accuracy, and relevance.
• Translate business requirements into technical LLM capabilities.
• Collaborate with Product, Data Science, and Engineering teams for AI alignment.
• Share best practices with architecture and engineering teams.

Skills

Problem-solving

Critical thinking

Communication

Team collaboration

Agile mindset

Adaptability

Learning agility

Multilingual communication

Leadership

Mentoring

Education

Bachelor’s degree in CS/AI/Data Science

Master’s degree in CS/AI/Data Science

Tools

LangChain

Unsloth

HuggingFace

FAISS

Pinecone

Arize AI

WandB

PyTorch

TensorFlow

PEFT techniques

Job description

DOKU, PT NUSA SATU INTI ARTHA is seeking an AI Expert to fine-tune, deploy, and optimize LLM-based chatbot systems. You will build scalable pipelines, implement observability, and balance latency, cost, and accuracy across multilingual financial use cases.

The role requires 3–5 years of AI/ML experience, strong knowledge of LangChain, Unsloth, and popular frameworks, and the ability to translate business needs into AI capabilities. Onsite collaboration with product and data teams is expected.