LLM Engineer

About the Role

The Kuala Lumpur office is the technology powerhouse of MoneyLion. We pride ourselves on innovative initiatives and thrive in a fast-paced and challenging environment. Join our multicultural team of visionaries and industry rebels in disrupting the traditional finance industry!

We are looking for an LLM Engineer to develop and optimize AI models specifically within the domain of large language models that will enable us to innovate and deliver generative AI applications.

As an LLM Engineer, you will have the opportunity to leverage Large Language Models (LLMs) and state-of-the-art techniques to deliver on Generative AI (GenAI) use cases. You will play a critical role in deploying, optimizing, and scaling GenAI applications to ensure they perform efficiently and reliably in a production environment. This position offers the opportunity to work closely with Applied Scientists, Data Scientists, and Product teams to bring cutting-edge GenAI solutions to life and scale them to handle ever increasing load.

This article goes over how we envision our LLM Application Stack to look like in the future, in which this role will be responsible for integrating and improving it over time.

Key Responsibilities

• Design, implement, and maintain robust, scalable, and efficient GenAI application infrastructure
• Deploy LLMs and other Machine Learning models into production, ensuring high availability and performance
• Develop and maintain caching layers to optimize the performance of GenAI applications
• Implement monitoring and logging systems to track model performance and system health
• Collaborate with Data Scientists to integrate models into existing systems and workflows
• Optimize model inference times and resource utilization to handle large-scale data efficiently
• Ensure best practices in Software Engineering, including testing, CI/CD, clean code are applied to Machine Learning projects
• Work with cross-functional teams to understand business requirements and translate them into technical solutions
• Troubleshoot and resolve issues related to model deployment and system integration
• Stay updated with the latest advancements in GenAI, machine learning infrastructure, and distributed system

About You

• Strong background in software engineering with a focus on machine learning infrastructure
• Proficient in deploying, scaling, and optimizing Machine Learning models in a production environment
• Solid understanding of distributed systems, microservices architecture, and cloud platforms (e.g., AWS, GCP, Azure)
• Hands-on experience with containerization technologies like Docker and orchestration tools like Kubernetes
• Proficient in Python and experience with other programming languages such as Java, C++, or Go is a plus
• Strong knowledge of CI/CD pipelines, coding best practices, version control systems, and DevOps practices
• Familiarity with GenAI technologies and frameworks, and a keen interest in their development and application
• Excellent problem-solving skills and ability to work independently on projects from end-to-end
• Strong verbal and written communication skills to effectively collaborate with cross-functional teams and stakeholders
• Have a growth mindset where you always want and try to improve processes/systems for the better
• Able to work end-to-end from ideation all the way to execution with minimal supervisior

What's Next...

After you submit your application, you can expect the following steps in the recruitment process:

1. Online Technical Test
2. Take-Home Assessment
3. Interview & Discussion of Take-Home Assessment - Hiring Manager (Virtual or face-to-face)

*If you’ve already sent in your application for this position and were not selected, please re-apply after 6 months.*