AI Machine Learning Engineer (Financial Institution)
Description
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
