全职 Lead LLM Engineer 工作, 薪水 up to MYR 8,000, SRKay Consulting Group 50470 公司招聘中 - Ricebowl

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).

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.