Manufacturing AI Engineer

到岗时间：不限 婚况要求：不限 We are looking for a Senior Machine Learning Engineer based in Jiangmen to build and deploy AI solutions for manufacturing scenarios, including predictive maintenance, quality prediction, and process optimization. You will work end-to-end across the ML lifecycle, from data preparation to model deployment, and collaborate closely with business and operations teams to bring AI into real production environments. Key Responsibilities ● Design, develop, train, and deploy machine learning models to support AI applications in manufacturing, such as predictive maintenance, quality prediction, and process optimization. ● Perform data collection, cleaning, preprocessing, and feature engineering to ensure high-quality input data for modeling. ● Conduct model selection, hyperparameter tuning, evaluation, and continuous optimization to improve model accuracy, robustness, and stability in production. ● Collaborate with business stakeholders, production, and IT teams to understand requirements and translate them into AI solutions that can be integrated into existing systems. ● Support end-to-end MLOps practices, including model deployment, monitoring, versioning, and automated retraining using tools such as Docker and Kubernetes. ● Prepare clear technical documentation and reports, and share best practices for model development and deployment within the team. Qualifications ● Bachelor’s degree or above in Computer Science, Applied Mathematics, Data Science, Statistics, or a related field. ● Minimum 2 years of hands-on experience in machine learning projects, preferably with end-to-end model development and deployment. ● Strong programming skills in Python and experience with mainstream ML libraries such as scikit-learn, XGBoost, and LightGBM; familiar with data analysis tools like Pandas, NumPy, and visualization libraries such as Matplotlib/Seaborn. ● Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch) and solid understanding of machine learning theory, including supervised and unsupervised learning, time-series forecasting, and model evaluation methods. ● Proficient in SQL and experienced in statistical analysis techniques (e.g., hypothesis testing, regression analysis, clustering). ● Understanding of MLOps concepts and tooling, including containerization and model serving using Docker, Kubernetes, or similar platforms. ● Experience in manufacturing or industrial AI scenarios (e.g., predictive maintenance, quality inspection/prediction, production line optimization) is a strong plus. ● Strong problem-solving skills, ability to work with cross-functional teams, and willingness to be based full-time in Jiangmen.