Research Engineer (AI Infrastructure) - Large Model Applications - Global Frontier Tech Recruit[...]

TikTok; Singapore; On-site; SGD 70,000 - 90,000; Full time

Job summary

TikTok is looking for talented individuals for a graduate role in Singapore focusing on the design and development of the Recommendation and Search system architecture. Candidates must have recently completed or be completing a PhD in AI, Computer Science, or related fields. Proficiency in programming (C/C++ or Python) is essential, alongside strong knowledge of data structures and algorithms. Join TikTok to innovate and tackle complex challenges in generative AI infrastructure.

Qualifications

• Recent PhD graduates or current PhD students in relevant fields.
• Strong programming skills in C/C++ or Python.
• Data structures and algorithms knowledge required.

Skills

Programming abilities

C/C++ proficiency

Python proficiency

Data structures and algorithms

Engineering mindset

Education

PhD in Artificial Intelligence, Computer Science, Computer Engineering, or related discipline

Job description

Responsibilities

We are looking for talented individuals to join our team in 2027. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at our Company.

Successful candidates must be able to commit to an onboarding date by end of year 2027. Please state your availability and graduation date clearly in your resume.

Team Introduction: Our Team is responsible for the design and development of the Recommendation and Search system architecture for TikTok. It ensures the stability and high availability of the system, optimizes the performance of online services and offline data streams, resolves system bottlenecks, and reduces cost overheads. The team also abstracts the common components and services of the system, builds the recommendation middle‑office and data middle‑office to support the rapid incubation of new products and enable ToB services.

Topic Content: As business scenarios become increasingly complex, search, advertising, and recommendation are facing significant challenges. While large models can accurately capture user preferences and enhance personalization as well as content quality, they also impose stringent requirements on real‑time performance, stability, and scalability. This introduces substantial technical challenges in areas such as distributed training, inference acceleration, heterogeneous hardware utilization, and multimodal data processing. At the same time, the rapid growth in model scale and the proliferation of multimodal data have made it difficult for existing infrastructure to meet the demands of data processing efficiency and resource utilization. This topic focuses on system and engineering innovations to overcome key technical bottlenecks and build efficient, stable, and scalable large‑model solutions, providing a robust technical foundation for search, advertising, and recommendation scenarios.

Topic Challenges

• Native training and inference architecture redesign for LLMs
• Etreme performance optimization and AI infrastructure innovation
• End‑to‑End generative paradigm innovation
• Multimodal AU data infrastructure and quality optimization
• Multimodal data representation and RAG‑based application system

Topic Value

Building next‑generation generative AI infrastructure for search, advertising, and recommendation businesses. Through the co‑design of large models, multimodal technologies, and system‑level innovations, we aim to overcome performance bottlenecks and enable ultra‑long context handling, millisecond‑level response latency, and high‑precision information understanding, thereby driving intelligent upgrades across the business.

Qualifications

Minimum Qualifications

• Individuals who are completing or recently completed a PhD in Artificial Intelligence, Computer Science, Computer Engineering, or a related technical discipline.
• Excellent programming abilities with a strong command of data structures and fundamental algorithms. For traditional coding roles, proficiency in C/C++ is required; for intelligent coding roles, proficiency in Python is required. Candidates are required to use these languages to implement complex algorithms and build iterative models. Candidates should also have a strong engineering mindset with the ability to balance performance and cost.

Preferred Qualifications

• Candidates with publications in CCF‑A category journals or conferences such as VLDB, SIGIR, OSDI, etc., are preferred.
• Strong resilience, excellent communication and teamwork skills; passionate about technology, willing to embrace challenges with the team, and a drive for innovation.

Job Information

About TikTok: TikTok is the leading destination for short‑form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.