Working hour: 9:00 am to 6:00 pm (Monday to Friday)
Position: AI Engineer Intern
Location: Di An, Binh Duong/ Tan Binh, HCM
Level: Fresher/Intern
Job Description
Support deployment and monitoring of ML models (using tools like Docker, Kubernetes, MLflow, or cloud services).
Develop and optimize ML models for tasks such as classification, regression, or risk prediction (e.g., loan approval, credit scoring).
Implement ML pipelines: Automate data processing, training, validation, and model evaluation.
Collaborate with engineers and data scientists to integrate models into production environments (APIs, microservices).
Research and prototype new features or algorithms to improve system accuracy and efficiency.
Document and communicate results clearly in code and presentations.
Work with tabular/structured data: Data cleaning, feature engineering, and exploratory data analysis (EDA) using tools like Pandas, NumPy, and visualization libraries (e.g., Matplotlib, Seaborn).
Job Requirements
Technical Skills
Knowledge of model evaluation metrics: Accuracy, AUC, F1, Precision/Recall, etc.
Basic understanding of Machine Learning algorithms: Especially those suitable for tabular data (e.g., Logistic Regression, Decision Trees, Random Forest, XGBoost, CatBoost, LightGBM, SVM).
Good knowledge of Python (and/or R, C++/Java is a plus).
Willingness to learn and apply new AI/ML concepts quickly.
Hands- on experience with data processing/analysis using Pandas, NumPy; able to handle missing data, outliers, feature selection, encoding, etc.
Good at English communication
Familiarity with ML frameworks: scikit- learn, and optionally PyTorch or TensorFlow for more advanced tasks.
Familiar with version control (Git) and basic software development workflows.
Nice to Have (Plus)
Experience in AI model deployment (Flask/FastAPI, Docker, or cloud platforms: AWS/GCP/Azure).
Prior participation in Kaggle competitions or ML projects (especially those with tabular data).
Knowledge of SQL/NoSQL databases for data querying.
Familiar with MLOps concepts, CI/CD for ML, or tools like MLflow, DVC.
Exposure to business problems in finance, banking, or loan risk modeling is a strong plus.
Benefits:
Potential full- time employment after internship.
Opportunity to work with state- of- the- art AI & ML technologies.
Networking with top AI professionals and working in an international environment.
Mentorship from senior AI engineers and industry experts.
Hands- on experience in AI software design and deployment.
