Nvidia Senior Data Scientist 

Taiwan, Taipei 

129303022

What you'll be doing:

• Developing a high-performance, highly available real-time analytics system for both internal teams and external partners.

• Designing and building various services and agentic applications utilizing diverse AI models and machine learning techniques to address challenges in GPU server manufacturing.

• Continuously improving AI/ML model performance through ongoing finetuning or training.

• Participating in planning and design meetings with stakeholders, offering professional suggestions, and consistently tracking follow-up actions.

What we need to see:

• BS or MS in Computer Science, Artificial Intelligence, or equivalent experience

• 6+ years of demonstrable experience in AI / ML

• Expertise in the full lifecycle of AI model development, from training to real-world production deployment, with a deep understanding of machine learning algorithms.

• Proficient in developing sophisticated agentic applications, especially those using RAG architecture or MCP protocol.

• Comprehensive knowledge and hands-on experience with various ML strategies (Regression, Classification, Clusterization), understanding their principles and optimal use.

• Proven track record in designing, implementing, and maintaining robust, scalable distributed systems for large data and computational demands.

• Strong ability to clearly articulate complex technical concepts to diverse audiences and collaborate effectively.

• Highly proficient in spoken and written English for international professional communication.

• Self-motivated, takes initiative, owns tasks, delivers high-quality results, and meets deadlines consistently.

Ways to stand out from the crowd:

• Proficient in programming languages such as Python, R, or C/C++.

• Experienced with the Linux development environment.

• Familiar with data science libraries and tools, including scikit-learn, SciPy, NumPy, pandas, Matplotlib, PyTorch, natural language processing (NLP), and searching/indexing techniques.

• Skilled in SQL and other data query languages.

• Knowledgeable in various database systems (SQL, NoSQL, embedding databases, etc.).