Focus on transitioning machine learning models from development to business applications, ensuring high performance and successful integration into existing systems.

Collaborate with business users, developers, infrastructure teams, and external partners to create machine learning models that meet specified business requirements and performance targets.

Design and implement machine learning inference processes to run models on live data and generate actionable outputs efficiently.

Prepare technical documentation and reports.

Participate in project meetings to update on task progress and follow up on actions.

Degree in Computer Science, Data Science, or a related field.

At least 6 years of IT experience, with a minimum of 2 years in deploying and performance tuning AI models (specifically for text analytics) and delivering complex data integration projects.

Strong knowledge of supervised machine learning algorithms, particularly BERT LLM and LightGBM Random Forest models.

Proficiency in Python programming, utilizing essential libraries such as NumPy, Pandas, Scikit-learn, and PyTorch. Familiarity with the ONNX framework for model deployment and Flask API development is a plus.

Excellent problem-solving skills.

Strong communication and presentation abilities.

Experience in designing and implementing web applications using Java, Spring Boot, Spring Data/JPA, and Oracle databases is a significant advantage.

Proficient in both spoken and written English and Chinese.