LLM Engineer: Build, Fine-Tune & Deploy Real‑World AI

KDCI Outsourcing

Pasig

Presencial

PHP 1.000.000 - 2.000.000

Jornada completa

14 días+

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Descripción de la vacante

KDCI Outsourcing is seeking an LLM Engineer to design, fine-tune, and deploy large language model solutions across the model lifecycle. You will collaborate with product and engineering teams to ship reliable AI features from prompt design to production monitoring.

Ideal candidates have 3+ years of hands-on NLP/LLM experience, strong transformer knowledge, and proficiency in Python with PyTorch or TensorFlow.

Formación

  • 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.

Responsabilidades

  • 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

Conocimientos

LLM/NLP experience
Transformer architectures
Python
PyTorch
TensorFlow
Fine-tuning
Prompt engineering
Hyperparameter optimization
Production ML/LLM

Herramientas

PyTorch
TensorFlow

Descripción del empleo

KDCI Outsourcing is seeking an LLM Engineer to design, fine-tune, and deploy large language model solutions across the model lifecycle. You will collaborate with product and engineering teams to ship reliable AI features from prompt design to production monitoring.

Ideal candidates have 3+ years of hands-on NLP/LLM experience, strong transformer knowledge, and proficiency in Python with PyTorch or TensorFlow.

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