Machine Learning Engineer

Location: Hong Kong
Contract: 1-Year Contract | Highly Renewable

About the Role

We are seeking a Machine Learning Engineer on behalf of our client to design, develop and deploy production-grade ML and AI solutions. You will work across the full ML lifecycle, from model development and experimentation through to deployment, monitoring and optimization.

Key Responsibilities

• Design, develop and deploy machine learning models into production.
• Perform data preprocessing, feature engineering, model training and evaluation.
• Build and maintain ML pipelines and MLOps workflows.
• Develop scalable model-serving APIs and inference solutions.
• Deploy ML applications using Docker/Kubernetes and cloud platforms.
• Develop Generative AI / LLM / RAG solutions.
• Monitor model performance, data quality and model drift.
• Collaborate with Data Scientists, Data Engineers, Software Engineers and business stakeholders.

Mandatory Skills & Experience

• 4+ years of experience in Machine Learning / AI Engineering.
• Strong Python programming skills.
• Hands-on experience with PyTorch, TensorFlow or scikit-learn.
• Proven experience deploying ML models into production.
• Strong experience in MLOps, ML pipelines and model deployment.
• Experience with Generative AI / LLM / RAG.
• Experience with LangChain, LangGraph or similar AI frameworks.
• Experience with Hugging Face or equivalent LLM/model libraries.
• Experience with vector databases such as FAISS, Pinecone, Milvus or Qdrant.
• Experience with Docker and Kubernetes.
• Experience with at least one cloud platform: AWS, Azure or GCP.
• Strong SQL and data processing experience.
• Good understanding of Git, REST APIs and CI/CD.
• Bachelor's degree in Computer Science, AI, Data Science, Engineering, Mathematics or related discipline.

Preferred

• Experience with MLflow / Kubeflow.
• Experience with Spark / Airflow.
• Experience with GPU-based model training or inference.
• Experience in banking, financial services or other enterprise environments.