AI Engineer

The AI Engineer (DS3) is responsible for designing, developing, deploying, and optimizing AI/ML/GenAI models to solve complex business problems in banking. This role works closely with data scientists, data engineers, and business teams to deliver scalable, production-ready AI solutions.

• Design, develop, and deploy AI/ML/GenAI models for banking use cases such as fraud detection, customer personalization, credit scoring, risk management, and operational optimization.

• Participate in the end-to-end AI model lifecycle, including data processing, training, evaluation, testing, deployment, and monitoring.

• Apply advanced analytics techniques such as machine learning, deep learning, NLP, computer vision, and GenAI to real-world business problems.

• Collaborate with Data Scientists, Data Engineers, and Platform teams to ensure models are scalable and production-ready.

• Implement and contribute to MLOps/LangOps pipelines, including CI/CD for models, versioning, monitoring, and retraining.

• Optimize model performance, reliability, and interpretability to meet business and regulatory requirements.

• Work with cloud-based platforms (AWS, Azure, GCP, Databricks) to deploy AI solutions securely and efficiently.

• Document models, experiments, and technical designs clearly for reuse and governance

• 3–5 years of experience in advanced analytics, machine learning/deep learning, and/or applying AI/GenAI to business problems.

• Proven experience in independently developing analytical models supporting objectives such as business growth, personalization, operational optimization, customer experience enhancement, or fraud detection.

• Hands-on experience deploying AI/ML/GenAI models or applications on cloud platforms (AWS, Azure, GCP, Databricks, etc.).

• Strong knowledge of statistical modeling, machine learning, deep learning, and GenAI algorithms.

• In-depth experience with advanced analytics techniques: hypothesis testing, causal inference, handling imbalanced data, time series analysis, inferential modeling, and vector embeddings.

• Proficiency in Python and AI/ML/GenAI libraries such as Scikit-learn, XGBoost, LightGBM, PyTorch, TensorFlow, Hugging Face Transformers.

• Experience with deployment and engineering tools such as MLflow, Docker, Git.

• Solid understanding of MLOps/LangOps, including data pipelines, model deployment, monitoring, and lifecycle management.

• Experience working in large organizations, banks, or technology companies is preferred.

• Preferred candidates with experience in NLP, Computer Vision, or Speech Processing.

• Salary: Negotiable

• Bonuses: Public holidays, Tet bonus, and at least 13th-month salary per year.

• Insurance: Full Social Insurance (SI) and Health Insurance (HI) in accordance with labor law.

• Leave: Annual leave as per Vietnamese labor regulations.

• Working environment: Professional and international working environment.