Responsibilities:
Gain a basic understanding of a broad area of research and applicable research techniques, as well as a basic knowledge of industry trends and share your knowledge with immediate team members.
Apply strategies provided by Senior team members. Following guidance from team leaders, research relevant tools and technologies being used in the community.
Reinforce a positive environment by learning and adopting best practices. Maintain & develop ties with an external network of peers and identify prospective talent for our research pipelines.
Assist with documentation for senior team members. Learn and follow ethic and privacy policies while exeuctive research processes or collecting information.
Required Qualifications:
A Bachelor's degree in Computer Science, Computer Engineering, Infromation Systems, Industrial Engineering or Data Science.
Currently pursuing M.Sc. or Ph.D. in Data Science or related field AND relevant internship experience (e.g. statistics, predictive analytics, research in Machine Learning).
Proficiency in using Python and SQL.
Strong theoretical bacground in classical Machine Learning and Deep Learning.
Hands-on experience working with Large Language Models (LLMs): building applications, conducting experiments, and being familiar with techniques to evaluate their performance.
Must have at least 3 semesters remaining for graduation (graduation date: January 2026 and onward).
Preferred Qualifications:
Experience in setting up and working in Cloud environment.
Relevant publications in machine learning / NLP / data mining journals and conferences (e.g., ICML, KDD, AAAI, NeurIPS, ICLR, ACL, WSDM, ICDM).
Experience with deep learning frameworks such as Pytorch.
Previous experience as an ML or MLOps Engineer.
