AI Machine Learning Engineer (Financial Institution)

Recruit Squad Limited; Hong Kong; On-site; HKD 900,000 - 1,300,000; Full time

Job summary

Recruit Squad Limited in Hong Kong is seeking an AI Machine Learning Engineer to lead a small team of engineers in designing scalable AI platform architectures, on premise or cloud-native. You will drive MLOps, LLMOps and AgentOps to streamline the AI lifecycle.

Collaborate with Data Scientists to optimize model performance and deploy infrastructure as code. You will conduct PoCs for new AI technologies and ensure AI platforms meet security and privacy standards in a financial services context.

Qualifications

• University degree in computer science, software engineering, or related fields.
• At least 3 years of AI/ML platform development with a strong background in software engineering.
• Deep understanding of AI and machine learning concepts and technologies (e.g.: RAG pipelines, LoRA, Harness Engineering, etc)
• Experience with MLOps, LLMOps and AgentOps
• Experience in delivery of AI platform or data platform with GPU infrastructure
• Excellent problem-solving skills and ability to optimize complex AI systems
• Familiarity with data privacy and security best practices for AI applications
• Excellent communication skills and data driven thinking capabilities
• Experience in working in an international team, with solid grounding in financial service is a plus
• Fluent in English, Cantonese, and/or Mandarin
• Working location in Hong Kong

Responsibilities

• Lead and support a small team of engineers to design and implement scalable AI platform architectures either on premise or using cloud-native technologies.
• Implement MLOps, LLMOps and AgentOps practices to streamline the AI development lifecycle.
• Collaborate with Data Scientists and AI Engineers to optimize model performance and resource utilization.
• Develop and maintain infrastructure as code (IaC) for AI platforms.
• Conduct proof-of-concept projects for new AI technologies and platforms.
• Work closely with cross-functional teams to align AI platform capabilities with business requirements

Skills

Problem-solving

Communication

Data-driven thinking

Team leadership

Cross-functional collaboration

Education

Bachelor's degree in Computer Science or related field

Tools

Python

SQL

Bash

PowerShell

Jenkins

JIRA

Sonar

Git

Ansible

Nexus

Harbor

JMeter

JUnit

PyTest

Jupyter

MLFlow

Ray

vLLM

Weaviate

Dify

Job description

AI Machine Learning Engineer (Financial Institution)

Lead and support a small team of engineers to design and implement scalable AI platform architectures either on premise or using cloud-native technologies.

Implement MLOps, LLMOps and AgentOps practices to streamline the AI development lifecycle.

Collaborate with Data Scientists and AI Engineers to optimize model performance and resource utilization.

Develop and maintain infrastructure as code (IaC) for AI platforms.

Conduct proof-of-concept projects for new AI technologies and platforms.

Work closely with cross-functional teams to align AI platform capabilities with business requirements.

Requirements

University degree in computer science, software engineering, or related fields

At least 3 years of experience in AI/ML platform development with a strong background in software engineering

Deep understanding of AI and machine learning concepts and technologies (e.g.: RAG pipelines, LoRA, Harness Engineering, etc)

Experience with MLOps, LLMOps and AgentOps

Experience in delivery of AI platform or data platform with GPU infrastructure

Excellent problem-solving skills and ability to optimize complex AI systems

Familiarity with data privacy and security best practices for AI applications

Excellent communication skills and data driven thinking capabilities

Experience in the following technology stack is a plus:

Scripting: Python, SQL, Bash and Powershell

DevSecOps Suite: Jenkins, JIRA, Sonar, Git, Ansible, Nexus, Harbor

Test Framework: jMeter, jUnit, PyTest

AI Platform: Jupyter, MLFlow, Ray, vLLM, Weaviate, Dify

Experience in working in an international team, with solid grounding in financial service is a plus

Fluent in English, Cantonese, and/or Mandarin

Working location in Hong Kong