Deep Learning Researcher (PhD & Chinese speaking)
The Deep Learning Researcher role focuses on developing and refining deep learning and machine learning models to analyse complex datasets. This position is integral to advancing our client’s data modelling capabilities within a collaborative and innovative environment.
About the Company
[Limited data provided — review with hiring manager before publishing].
Role Overview
The successful candidate will employ deep learning and machine learning techniques to uncover patterns and improve model performance. The role involves implementing models using PyTorch or TensorFlow, with a focus on continuous optimisation and pattern recognition. Reporting initially to the team leads, the researcher will be responsible for delivering high-quality data modelling solutions and insights within an on-site setting. Success will be measured by the accuracy and robustness of developed models.
Key Skills & Experience
- Implement various deep learning and machine learning techniques for data modelling
- Identify data patterns and intrinsic logic, ensuring continuous model optimisation
- Possess advanced programming skills in PyTorch or TensorFlow
- Hold a Ph.D. degree in Computer Science, Mathematics, Statistics, Physics, or related STEM fields from a top-tier university
- Show prior achievements in academic competitions, especially Kubernetes or Kaggle
Nice to Have
[Limited data provided — review with hiring manager before publishing].
Key Responsibilities
- Develop and refine deep learning models using PyTorch or TensorFlow
- Discover and analyse data patterns to inform model improvements
- Manage the deployment of models in an on-site environment
- Collaborate with team members to ensure model performance aligns with project objectives
Requirements
- Right to work in the specified location
- Ph.D. degree in relevant STEM discipline from a top-tier university
- Proficiency with PyTorch or TensorFlow
- Ability to work on-site in Asia
- Availability to commence from 11/08/2026 for a duration of 2 weeks
If you have the relevant skills and experience, please apply with an updated CV.
