AI Engineer

4 days ago

Kwai Chung, Hong Kong SAR China Gemini Personnel Group Limited Full time

Model Development: Design and develop AI/ML models to optimize terminal operations, e.g. Dwell Time Prediction, Yard Planning and Usage Optimization, and Resource Allocation Automation (e.g. Cranes, Internal Tractors, etc). Responsibilities: Model Development: Design and develop AI/ML models to optimize terminal operations, e.g. Dwell Time Prediction, Yard Planning and Usage Optimization, and Resource Allocation Automation (e.g. Cranes, Internal Tractors, etc). Data Analysis: Collect, preprocess, and analyze large datasets from terminal operations to identify patterns and provide insights and recommendations. Automation: Implement AI-driven solutions for automating processes such as berth allocation, crane job assignment, and traffic flow within the terminal. Real-Time Systems: Develop and deploy real-time AI models for dynamic decision-making in terminal operations, such as Congestion Prediction and Shortest Route calculation. Performance Monitoring: Monitor and evaluate the performance of deployed models, ensuring Accuracy, Scalability, and Reliability in production environment. Research and Innovation: Stay updated on the latest advancements in AI/ML and propose innovative solutions to improve operational efficiency and sustainability. Collaboration: Work closely with cross-functional teams, including data scientists, data engineers, software engineers, and operations managers, to integrate AI/ML solutions into existing systems. Requirements: Bachelors degree in an IT-related discipline. Data Science, Artificial Intelligence, Machine Learning, or a related field is a plus. 6+ years of experience in developing and deploying AI/ML models in real world applications. Experience with Time-Series data, CV (Computer Vision), NLP (Natural Language Processing) and Prompt Engineering is a plus. Familiarity with logistics, supply chain, or terminal operations is highly desirable. Proficiency in Python, R, or similar programming languages. Strong experience with ML frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience with specific models like LLM (Large Language Model), LSTM (Long Short-Term Memory), ARIMA (Autoregressive Integrated Moving Average), XGBoost, Random Forest, RL (Reinforcement Learning), GNNs (Graph Neural Networks), CNNs (Convolutional Neural Networks), ANNs (Artificial Neural Networks) or anomaly detection models (e.g. Autoencoders, Isolation Forests). Knowledge of big data tools (e.g. Hadoop, Spark, Databricks) and cloud platforms (e.g. AWS, Azure, Google Cloud). Experience with database systems (SQL, NoSQL) and data preprocessing techniques. Experience with IoT and sensor data integration is a plus. Strong problem-solving and analytical skills. Ability to work in a fast-paced, dynamic environment. Fluent in written and verbal English, demonstrated communication and stakeholder management skills. For more information about this job opportunity please contact our consultant. #J-18808-Ljbffr

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