AI Machine Learning Engineer (Financial Institution)

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.

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

• Infrastructure: Docker, Terraform, Helm, Kubernetes

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

• Test Framework: jMeter, jUnit, PyTest

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

• AI Model: Gemma, Deepseek, Qwen, GLM, etc.

• Monitoring: Grafana, Loki, Prometheus, Promptail

• 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