Responsibilities
- Design and implement AI/ML models for infrastructure optimization, predictive analytics, and anomaly detection
- Develop machine learning pipelines for server performance prediction, automated incident response, and resource allocation
- Build and maintain AI-powered monitoring systems using frameworks like TensorFlow, PyTorch, or scikit-learn
- Collaborate with DevOps and Systems teams to integrate ML models into production environments
- Conduct data analysis and model evaluation to improve system reliability and reduce downtime
- Participate in AI research and stay updated with latest machine learning trends
- Mentor junior engineers on best practices in ML development and deployment
Requirements
- Bachelor's degree in Computer Science, Mathematics, Statistics, or related field
- 2+ years professional experience in machine learning/AI development
- Strong proficiency in Python, with experience in data science libraries (NumPy, Pandas, Scikit-learn)
- Experience with deep learning frameworks (TensorFlow, PyTorch, or Keras)
- Solid understanding of statistical methods, algorithms, and model evaluation techniques
- Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes)
- Knowledge of time-series analysis and anomaly detection is highly preferred
- Familiarity with MLOps tools (MLflow, Airflow, Jenkins) is a plus
- Strong problem-solving skills and ability to work in agile environments
- Excellent communication and documentation skills
Apply for this roleEmail your CV to hr@ud.hk · quote reference UD-AIME-26