# LLM Engineer at KDCI

> Hybrid · Philippines · Unspecified · ML / AI · open. Source: https://alderhq.app/jobs/recruitee%3Akdci1%3A2682325 (read 2026-11-08).

## Facts (observed)

- Company: [KDCI](https://alderhq.app/companies/kdci)
- Location text: Pasig City, National Capital Region, Philippines
- Where it can be done from (inferred): Hybrid · Philippines (evidence: "Location: Pasig City, National Capital Region, Philippines")
- Posted: 2026-07-20 (111 days ago)
- First seen by alder: 2026-11-07 · last verified: 2026-11-08
- Reposted: 0 times · edited: 0 times
- Apply on the employer's site: https://kdci1.recruitee.com/o/llm-engineer
- Skills listed (inferred): Python, PyTorch, TensorFlow, LLMs

## Pay and sponsorship

- Posted pay: not posted

## Description (the employer's text)

### Role Summary

KDCI Outsourcing is looking for an LLM Engineer to design, fine-tune, and deploy large language model solutions that solve real business problems. You'll work across the model lifecycle — from prompt and architecture design to evaluation and production monitoring — collaborating with product and engineering teams to ship reliable AI features.

### Key Responsibilities

Design, fine-tune, and optimize large language models for specific use cases

Build and maintain evaluation harnesses to measure model quality and safety

Implement RAG (retrieval-augmented generation) pipelines and prompt strategies

Monitor model performance in production and iterate on improvements

Collaborate with product and engineering teams to integrate LLM features

Stay current with emerging LLM research, architectures, and tooling

### Requirements

### Requirements

3+ years of hands-on experience with large language models and NLP

Strong understanding of transformer architectures (GPT, BERT, LLaMA, etc.)

Proficiency in Python and ML frameworks such as PyTorch or TensorFlow

Experience with fine-tuning, prompt engineering, and hyperparameter optimization

Track record of deploying ML/LLM systems in production environments

### Nice-to-Haves

Experience with vector databases and RAG pipelines

Familiarity with model quantization and inference optimization

Background in AI safety or content moderation systems

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Data: alder (https://alderhq.app). Cite https://alderhq.app/jobs/recruitee%3Akdci1%3A2682325 and the date you read it. Observed facts come from the employer's own listing; location reach, level, family and skills are inferences.