GenAI & MLOps Engineering Manager — Lead Scale & Ops

Randstad Hong Kong Limited; Hong Kong; On-site; HKD 1,100,000 - 1,500,000; Full time

Job summary

Randstad Hong Kong Limited is seeking a Machine Learning Engineering Manager to lead a distributed team across Hong Kong and Vietnam, driving production deployment, scaling, and operational excellence of ML, GenAI, and agentic AI architectures.

You will own technical milestones, delivery dependencies, and governance across MLE, while advancing CI/CD, MLOps, and cloud infrastructure. Fluency in English is required; Cantonese/Mandarin is a plus.

Qualifications

• Degree in Computer Science or related quantitative field.
• At least 1 year of formal people-management experience.
• Hands-on experience deploying and maintaining production ML/GenAI applications.
• Strong understanding of MLOps, LLMOps, CI/CD, and cloud platforms.

Responsibilities

• Lead end-to-end MLE delivery across AI projects from planning to deployment and production support.
• Own milestones, delivery dependencies, resource planning, and reliability across ML/GenAI systems.
• Establish standardised deployment workflows and automated testing.
• Enhance CI/CD, MLOps, and observability across cloud/data platforms.
• Guide architectural decisions and conduct design reviews.
• Manage and develop a distributed engineering team across locations.
• Identify bottlenecks and optimise deployment lead times.

Skills

MLEngineering

AI platform architecture

MLOps

LLMOps

CI/CD

Kubernetes/Docker

Cloud infrastructure

Team leadership

Machine learning

Software engineering

Education

Bachelor Degree

Tools

Azure

Databricks

Job description

Randstad Hong Kong Limited is seeking a Machine Learning Engineering Manager to lead a distributed team across Hong Kong and Vietnam, driving production deployment, scaling, and operational excellence of ML, GenAI, and agentic AI architectures.

You will own technical milestones, delivery dependencies, and governance across MLE, while advancing CI/CD, MLOps, and cloud infrastructure. Fluency in English is required; Cantonese/Mandarin is a plus.