Senior LLM Engineer

Srkay Consulting Group; Kuala Lumpur; On-site; MYR 120,000 - 240,000; Full time

Benefits offered by this job

EPF

SOCSO

Annual Leave

Medical Leave

Health Insurance

Job summary

Jora Malaysia is seeking an experienced LLM Engineer to design, develop, and deploy large language models and related AI systems. You’ll implement state-of-the-art architectures for NLP tasks, build robust APIs, and collaborate with product managers and data scientists to deliver innovative solutions.

You will write clean Python code for training, evaluation, and deployment pipelines, stay updated on NLP advancements, and troubleshoot complex model issues to ensure high availability and

Qualifications

• Design, develop, and deploy large language models and related AI systems.
• Implement and fine-tune state-of-the-art LLM architectures for NLP tasks.
• Develop robust APIs and integration points for LLM services.
• Write clean, efficient Python code for model training, evaluation, and deployment.
• Collaborate with cross-functional teams to define project requirements.
• Stay updated on LLM/NLP advancements and apply to improve systems.
• Troubleshoot and debug LLM models and infrastructure for high availability.
• Contribute to best practices and standards for LLM engineering.
• Experience with cloud platforms (AWS, Azure, GCP) for deploying AI models.
• Familiarity with MLOps and CI/CD for model lifecycle management.

Responsibilities

• Design, develop, and implement advanced LLMs and related AI systems to solve business problems.
• Collaborate with product managers and data scientists to define project requirements and deliverables.
• Fine-tune and optimize LLM architectures for specific tasks with performance and scalability.
• Develop and maintain robust APIs for integrating LLM capabilities into products.
• Stay abreast of NLP and ML advancements and apply them to improvements.
• Write clean Python code for model development, training, and deployment.
• Evaluate and benchmark LLM performance and implement improvements.
• Contribute to best practices and standards for LLM engineering.
• Troubleshoot and debug LLM models and their production integration.
• Mentor junior engineers on LLM development and deployment strategies.

Skills

LLM development

Python

NLP

Cloud platforms

MLOps

API development

Model deployment

CI/CD

Tools

AWS

Azure

GCP

CI/CD

Job description

Jora Malaysia will close on 9th September 2026. Thank you for being with us, we are cheering you on as you continue your career journey.

Design, develop, and deploy large language models (LLMs) and related AI systems, ensuring scalability and efficiency.

Implement and fine-tune state-of-the-art LLM architectures for various natural language processing tasks, including text generation, summarization, translation, and question answering.

Develop robust APIs and integration points to enable seamless interaction between LLM services and other software components.

Write clean, efficient, and well-documented Python code for model training, evaluation, and deployment pipelines.

Collaborate with cross-functional teams, including product managers, data scientists, and software engineers, to define project requirements and deliver innovative solutions.

Stay abreast of the latest research and advancements in LLM technology, NLP, and machine learning, and apply this knowledge to improve existing systems and explore new opportunities.

Troubleshoot and debug complex issues in LLM models and associated infrastructure, ensuring high availability and performance.

Contribute to the development of best practices and standards for LLM engineering within the organization.

Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying and managing large-scale AI models.

Familiarity with MLOps principles and tools for model lifecycle management, monitoring, and continuous integration/continuous deployment (CI/CD).

Requirement

• Design, develop, and deploy large language models (LLMs) and related AI systems, ensuring scalability and efficiency.

• Implement and fine-tune state-of-the-art LLM architectures for various natural language processing tasks, including text generation, summarization, translation, and question answering.

• Develop robust APIs and integration points to enable seamless interaction between LLM services and other software components.

• Write clean, efficient, and well-documented Python code for model training, evaluation, and deployment pipelines.

• Collaborate with cross-functional teams, including product managers, data scientists, and software engineers, to define project requirements and deliver innovative solutions.

• Stay abreast of the latest research and advancements in LLM technology, NLP, and machine learning, and apply this knowledge to improve existing systems and explore new opportunities.

• Troubleshoot and debug complex issues in LLM models and associated infrastructure, ensuring high availability and performance.

• Contribute to the development of best practices and standards for LLM engineering within the organization.

• Experience with cloud platforms (e.g., AWS, Azure, GCP) for deploying and managing large-scale AI models.

• Familiarity with MLOps principles and tools for model lifecycle management, monitoring, and continuous integration/continuous deployment (CI/CD).

Responsibility

• Design, develop, and implement advanced Large Language Models (LLMs) and related AI systems to solve complex business problems.
• Collaborate with cross-functional teams, including product managers and data scientists, to define LLM project requirements and deliverables.
• Fine-tune and optimize existing LLM architectures for specific tasks, ensuring performance, scalability, and efficiency.
• Develop and maintain robust APIs for integrating LLM capabilities into existing and new products and services.
• Conduct research and stay abreast of the latest advancements in LLM technology, natural language processing (NLP), and machine learning.
• Write clean, efficient, and well-documented Python code for model development, training, and deployment.
• Evaluate and benchmark LLM performance, identifying areas for improvement and implementing solutions.
• Contribute to the development of best practices and standards for LLM engineering within the organization.
• Troubleshoot and debug issues related to LLM models and their integration into production environments.
• Mentor junior engineers and share knowledge on LLM development and deployment strategies.

Benefits

• EPF
• SOCSO
• Annual Leave
• Medical Leave
• Health Insurance