Research Scientist Intern - LLM Applications for International E-commerce Scenarios - Global Fr[...]

TikTok; Singapore; On-site; SGD 33,480 - 55,800; Full time

Job summary

A leading technology company in Singapore seeks a PhD Intern to engage in innovative projects within the global e-commerce sector. This internship offers hands-on experience in developing advanced algorithms, integrating machine learning, and creating foundational large models tailored for e-commerce applications. Candidates should be pursuing a PhD in relevant fields with strong AI/ML expertise. Join a passionate team focused on technological innovation and collaboration.

Qualifications

• Currently pursuing PhD with a strong foundation in data structures and algorithms.
• Solid understanding and research experience in AI/ML fields.

Responsibilities

• Contribute to developing advanced recommendation algorithms.
• Work on integration of machine learning with operations research.
• Build foundational large models for e-commerce applications.
• Design scalable tokenization mechanisms for recommendation items.
• Establish metrics to evaluate agent systems for compliance.

Education

PhD in Computer Science, AI, Mathematics, or related discipline

Tools

Deep Learning

NLP

Computer Vision

Generative Models

Reinforcement Learning

Job description

Responsibilities

We are looking for talented individuals to join us for an internship in 2027. PhD Internships at our Company aim to provide students with the opportunity to actively contribute to our products and research, and to our organization’s future plans and emerging technologies. Our dynamic internship experience blends hands‑on learning, community‑building, development events, and collaboration with industry experts. Applications will be reviewed on a rolling basis – we encourage you to apply early. Please state your availability clearly in your resume (Start date, End date).

Team Introduction: The Data‑Global E‑Commerce team serves as the core technological engine for ByteDance’s Global E‑commerce. We specialize in pioneering algorithmic and big‑data innovations within the E‑commerce sector, driven by our mission: “To make a beautiful life readily accessible and to help unique, high‑quality products reach a global market.” Our work involves: developing advanced recommendation and search algorithms, leveraging risk‑control and platform governance technologies, constructing product knowledge graphs, integrating machine learning with operations research, and providing merchants with intelligent business tools.

Topic Content: In today’s global e‑commerce landscape, intelligent systems must operate across increasingly complex and dynamic business environments. We will build a next‑generation foundational large model for global e‑commerce applications, integrating users, products, content, logistics, and inventory into a unified representation to support deep, context‑aware intelligence at scale.

1. Heterogeneous fusion and alignment: Unified modeling of user behavior sequences, product sales time‑series signals, and multimodal product content to achieve deep semantic alignment across high‑dimensional temporal data and multimodal representations.
2. Synergy between recommendation LLMs and world models: Reformulate the recommendation problem as a generative task of producing ranked item lists for users, leveraging large‑model technologies to enable end‑to‑end recommendation modeling.
3. Tokenizer of recommendation items: Design scalable tokenization mechanisms to encode billions of items into multimodal and semantically rich representations, supporting training and generation tasks, and reframe diverse recommendation tasks as post‑training objectives.
4. Multimodal large models for e‑commerce: Develop multilingual, multimodal large models tailored for e‑commerce, achieving state‑of‑the‑art performance across core e‑commerce scenarios and building an e‑commerce agent backbone for scalable deployment of agent applications.
5. Agent evaluation, safety, and compliance: Establish evaluation metrics and benchmarks aligned with real‑world business scenarios to ensure the robustness, safety, and compliance of agent systems, particularly under highly constrained and adversarial conditions.

Qualifications

Minimum Qualifications

• Currently pursuing PhD in Computer Science, AI, Mathematics, or a related technical discipline, with a strong foundation in data structures, algorithms, and mathematical modeling.
• AI/ML Expertise: Solid understanding and research experience in Deep Learning, NLP, CV, Reinforcement Learning, Generative Models, or Multimodal Learning.

Preferred Qualifications

• Priority will be given to candidates with publications in international AI/CS conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR, ACL, KDD, SIGIR, WWW) or top rankings in recognized algorithmic competitions.
• Excellent programming abilities in leading or participating in key projects related to Search, Advertising, Recommendation systems, or Large Language Models (LLMs).
• Strong resilience, excellent communication and teamwork skills; passionate about technology, willing to embrace challenges with the team, and a drive for innovation.