Vietnam Silicon

Key Responsibilities

1. Assist in developing search systems using embeddings and basic reranking techniques under supervision.
2. Support the implementation and fine-tuning of deep learning models, applying standard loss functions with guidance.
3. Help create and organize datasets for model training and evaluation.
4. Contribute to the deployment and optimization of Large Language Models (LLMs) or Vision-Language Models (VLMs) in production environments.
5. Build simple interactive dashboards using Streamlit, Power BI, or Superset to visualize model outputs.
6. Participate in model performance evaluations using provided metrics and testing methodologies.
7. Collaborate with team members to understand and address business requirements through AI solutions.
8. Actively engage in team learning and contribute to Vietnam Silicon’s AI initiatives in the region.
9. Other tasks assigned by the Company or Line Manager

Requirements

1. Bachelor’s degree in Computer Science, Data Science, or a related technical field.
2. Basic understanding of mathematics, statistics, machine learning, and predictive modeling.
3. 1+ years of experience in machine learning or AI-related projects (including internships or academic work).
4. Familiarity with embedding technologies and vector search concepts.
5. Basic knowledge of statistical analysis and hypothesis testing.
6. Ability to work with deep learning architectures under supervision.
7. Experience with dataset preparation for AI applications.
8. Familiarity with Python and ML frameworks (PyTorch, TensorFlow, or Hugging Face).
9. Basic experience with tools like Streamlit for building dashboards.
10. Strong willingness to learn and good communication skills.
11. Ability to work collaboratively in a team environment.

Prefer

1. Exposure to GPU-based AI training environments.
2. Basic experience with fine-tuning language models.
3. Awareness of Southeast Asian languages or regional business contexts.
4. Contributions to open-source ML/AI projects or academic research.
5. Familiarity with enterprise AI applications.
6. Basic understanding of MLOps concepts.