PhD Machine Learning Researcher

Gravitas Recruitment Group Hong Kong; Los Angeles (CA); On-site; USD 120,000 - 180,000; Full time

Job summary

Gravitas Recruitment Group Hong Kong is seeking talented researchers to apply deep learning and machine learning techniques for modeling diverse datasets. The role focuses on uncovering patterns, intrinsic logic, and continuously refining models to achieve optimal performance.

The ideal candidate holds a Ph.D. in a STEM field, demonstrates strong PyTorch/TensorFlow programming skills, and has a track record in academic competitions or publications at top conferences/journals, with Kaggle

Qualifications

• PhD in Computer Science, Mathematics, Statistics, Physics or other STEM fields from a top-tier university.
• Outstanding programming skills with PyTorch or TensorFlow.
• Strong track record in research or competitions (e.g., Kaggle).
• Publications in top-tier ML conferences/journals (advantageous).

Responsibilities

• Implement a range of deep learning and machine learning techniques for data modeling.
• Identify data patterns and intrinsic logic, ensuring continuous model optimization.

Skills

Deep learning

Python programming

Model optimization

Education

Ph.D. in CS or STEM

Tools

PyTorch

TensorFlow

Job description

Role Overview: We are on the lookout for talented individuals who can employ a range of deep learning and machine learning techniques to model diverse datasets. The successful candidate will uncover patterns, seek inherent logic within data, and continuously refine models to achieve optimal performance.

What you'll do:

• Implement various deep learning and machine learning techniques for data modeling.
• Identify data patterns and intrinsic logic, ensuring continuous model optimization.

What you need:

• Graduates from top-tier universities, with Ph.D. degrees in Computer Science, Mathematics, Statistics, Physics, or other STEM fields.
• Outstanding programming skills with proficiency in Pytorch/Tensorflow. Able to swiftly develop and deploy cutting-edge deep learning models using one of these frameworks. Possesses the innovative capacity to refine and optimize models.
• Prior achievements in various academic competitions are preferred, especially with distinguished performance in renowned machine learning competitions like Kaggle.
• Publications in international top-tier conferences or journals in the fields of machine learning, data mining, recommendation systems, etc., including but not limited to NIPS, KDD, CVPR, ICML, ACL, AAAI, COLT, AISTATS, WWW, SIGIR, and IJCAI, will be a distinct advantage.