AI Machine Learning Engineer Intern (TikTok Search) - 2026 Start (PhD) Singapore PhD Intern- 20[...]

Ellis Technologies, Inc.; Singapore; On-site; SGD 33,480 - 66,960; Full time

Job summary

Ellis Technologies, Inc. is looking for a PhD Intern to join their search team in Singapore. You will be responsible for innovative contributions in NLP, machine learning, and computer vision to enhance TikTok's search engine capabilities.

The ideal candidate is pursuing a PhD in Computer Science and proficient in C++ and Python, with a strong background in AI. This internship is a fantastic opportunity to work on industry-leading technologies in a collaborative environment.

Qualifications

• Currently pursuing a PhD in a quantitative field.
• Proficient in C++ and Python.
• Strong AI and machine learning background.

Responsibilities

• Explore cutting-edge NLP technologies and multimodal systems.
• Engage in large-scale streaming machine learning for personalized search.
• Build high-availability, high-throughput online services.

Skills

C++

Python

Algorithms and Data Structures

AI/Machine Learning

NLP

Computer Vision

Education

Currently pursuing a PhD in Computer Science or related field

Job description

Team Introduction

Our Search Team is responsible for building and owning TikTok's search engine which provides our users the best search experience. On the TikTok Search Team, you’ll have the opportunity to build a full‑stack search engine system and combine information retrieval technology with modern machine learning methods from related fields such as NLP, Computer Vision, Multimodal, and Recommender Systems. We embrace a culture of self‑direction, intellectual curiosity, openness, and problem‑solving.

Responsibilities

As a PhD Intern, you will explore cutting‑edge NLP technologies, cross‑modal matching, large‑scale streaming machine learning, data architecture at scale, and recommendation technologies. Your contributions will involve deep learning models throughout the pipeline, semantic understanding and retrieval capabilities for multimodal video search, personalized search through multi‑modal and recommendation systems, and high‑availability, high‑throughput online services.

• Exploring cutting‑edge NLP technologies from word segmentation and named entity recognition to text and multimodal pre‑training, query analysis, and relevance modeling.
• Cross‑modal matching using deep learning techniques combining computer vision and natural language processing for powerful semantic understanding and retrieval for multimodal video search.
• Large‑scale streaming machine learning to address recommendation challenges in search, making the search more personalized.
• Researching and innovating in large‑scale offline computing and performance and scheduling optimization of distributed systems, building high‑availability, low‑latency online services.
• Building industry‑leading search recommendation systems and continuously exploring and innovating in search recommendation technologies.

Commit to a minimum of 3 months internship period.

Qualifications

• Minimum Qualifications: Currently pursuing a PhD in Computer Science, engineering or a quantitative field; proficient in C++/Python; strong command of algorithms and data structures; strong AI/machine learning background.
• Preferred Qualifications: Effective communication and teamwork skills; modeling experience in Ads, Search engine, Recommender System, NLP/CV; solid foundation in algorithms related to LLMs, including practical experience with single‑modal/multi‑modal LLM application and deployment.