
Algorithm Engineer Intern, Search Nlp
1 week ago
Department Engineering and Technology
- LevelInternship
- LocationSingapore
The Engineering and Technology team is at the core of the Shopee platform development. The team is made up of a group of passionate engineers from all over the world, striving to build the best systems with the most suitable technologies. Our engineers do not merely solve problems at hand; We build foundations for a long-lasting future. We don't limit ourselves on what we can or can't do; we take matters into our own hands even if it means drilling down to the bottom layer of the computing platform. Shopee's hyper-growing business scale has transformed most "innocent" problems into huge technical challenges, and there is no better place to experience it first-hand if you love technologies as much as we do.
**About the Team**:
This is a fast-growing opportunity to learn how state-of-the-art NLP and LLM technologies can solve real business problems and potentially deliver high-impact results during your internship.
We welcome passionate, self-driven individuals to join us in innovating and shaping the future of global search.
- Assist in algorithm experiments and performance evaluations to validate LLM effectiveness in real-world search scenarios.
- Learn and contribute to LLM optimization and deployment, including inference optimization and model distillation.
- Stay updated on the latest research in NLP and LLMs, and actively contribute to team discussions and innovations.
**Requirements**:
- Bachelor’s degree or above in Computer Science, Machine Learning, Statistics, Pattern Recognition, or related fields.
- Able to commit at least 3 months.
- Strong foundation in machine learning and NLP (e.g., Transformer, BERT).
- Proficiency in Python and familiarity with at least one deep learning framework (PyTorch/TensorFlow).
- Hands-on experience in model training or experimentation.
- Preferred (Nice-to-Have): Achievements in AI/NLP competitions (e.g., Kaggle, Tianchi), or experience in research publications or open-source projects.
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