- Focus on transitioning machine learning models from development to business application with high performance, ensuring successful deployment of the models and integration into existing systems and infrastructure
- Collaborate with business users, developers, infrastructure team and relevant external parties to work on machine learning models that can meet the target business requirements and performance.
- Design and implement machine learning inference for running the models to work on live data and produce an actionable output efficiently.
- Prepare technical documents and reports.
- Participate in project meetings to report responsible tasks progress and follow-up actions
Requirements:
- Degree holder in Computer Science, Data Science or relevant discipline;
- At least 6 years of IT work experiences with minimum 2 years of practical experiences in deployment / performance tuning of AI models (for text analytics) and delivering complex data integration projects
- Knowledgeable in supervised machine learning algorithms particularly BERT LLM and LightGBM Random-forest model
- Proficiency in Python programming using essential libraries such as NumPy, Pandas, Scikit-learn, PyTorch, etc. Familiar with ONNX framework for model deployment and FLASK API python development are a plus
- Capable of design and implementation of web application using Java, Spring Boot, Spring Data / JPA and Oracle database is definite an advantage.
- Excellent problem-solving abilities
- Strong communication and presentation skill;,
- Good communication skill in both spoken and written English and Chinese.