Company Description FiinGroup (formerly StoxPlus) is Vietnam's leading integrated provider of financial data, business information, industry research, and advanced data-driven analytics services. The company delivers comprehensive, high-quality insights to support decision-making for financial institutions, corporations, and investors. FiinGroup combines deep local market expertise with modern technology to create scalable data and analytics solutions. Team members join a dynamic environment that values innovation, analytical rigor, and practical applications of data and AI in the financial and business sectors.
Role Description The Applied AI Engineer is a full-time, on-site position based in Hanoi. This role focuses on designing, implementing, and deploying AI models and systems that enhance FiinGroup's data, analytics, and research products. Day-to-day responsibilities include building and optimizing machine learning pipelines, applying pattern recognition and neural networks to real-world financial and business data, and developing NLP solutions for extracting insights from text-based information. The engineer collaborates closely with data engineers, researchers, and product teams to translate business requirements into technical solutions, conduct experiments, validate models, and integrate AI components into production software. The role also involves monitoring model performance, improving robustness and scalability, and staying current with developments in applied AI to recommend new techniques and tools.
Qualifications
- Strong foundation in Computer Science, including algorithms, data structures, and software engineering principles.
- Experience with Pattern Recognition and Neural Networks for building and optimizing machine learning models.
- Hands-on skills in Natural Language Processing (NLP), especially for information extraction, text classification, or document understanding.
- Proficiency in Software Development, using languages such as Python, Java, or similar, and working with relevant ML/AI frameworks.
- Knowledge of applied machine learning workflows, including data preprocessing, feature engineering, model evaluation, and deployment.
- Familiarity with cloud platforms, APIs, and containerization tools (e.g., Docker, Kubernetes) is beneficial.
- Ability to collaborate effectively with cross-functional teams and communicate technical concepts clearly to non-technical stakeholders.
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field; experience in financial or business analytics domains is a plus.
