Vietnam Silicon

Job Brief

We are seeking a highly skilled and experienced Data Scientist with deep expertise in embedding technologies, deep learning architecture, and language model deployment. The ideal candidate will drive the development of our AI capabilities, lead technical innovation initiatives, and collaborate with cross-functional teams to deliver transformative AI solutions for our clients across Southeast Asia.

Responsibilities

1. Design and implement advanced search systems utilizing embeddings, hybrid search, cross-encoders, and reranking techniques
2. Architect, build, and fine-tune deep learning models from scratch, developing custom loss functions for specific use cases
3. Create, organize, and manage high-quality datasets for model training and evaluation
4. Develop interactive dashboards using Streamlit to visualize model performance and business outcomes
5. Conduct comprehensive evaluations of model performance with rigorous metrics and testing methodologies
6. Mentor junior team members and contribute to Vietnam Silicon's technical leadership in the region

Requirements

Must have

1. Bachelor degree/Master's degree in Computer Science, Data Science, or a related technical field
2. Strong in Math, statistic, machine learning, predictive models
3. 2+ years of professional experience in machine learning engineering or applied AI research
4. Demonstrated ability to design deep learning architectures and implement custom loss functions
5. Strong experience in dataset design, creation, and management for AI applications
6. Experience building interactive dashboards with Streamlit or similar tools
7. Advanced Python skills and expertise with major ML frameworks (PyTorch, TensorFlow, Hugging Face)
8. Excellent problem-solving and communication skills
9. Ability to work collaboratively with cross-functional teams

Prefer

1. Experience with GPU cluster management for distributed AI training
2. Expertise in fine-tuning large language models for specific domains
3. Familiarity with Southeast Asian languages and regional business contexts
4. Contributions to open-source ML/AI projects or research publications
5. Experience implementing AI solutions in enterprise environments
6. Knowledge of MLOps practices and tools for model deployment and monitoring