AI Infrastructure Engineer Graduate (TikTok Recommendation Architecture, Singapore) - 2027 Start

About Us

Founded in 2012, ByteDance's mission is to inspire creativity and enrich life. With a suite of more than a dozen products, including TikTok, Lemon8, CapCut and Pico as well as platforms specific to the China market, including Toutiao, Douyin, and Xigua, ByteDance has made it easier and more fun for people to connect with, consume, and create content.​

Why Join ByteDance

Inspiring creativity is at the core of ByteDance's mission. Our innovative products are built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and enrich life - a mission we work towards every day.​

As ByteDancers, we strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our Company, and our users. When we create and grow together, the possibilities are limitless. Join us.​

Diversity & Inclusion​

ByteDance is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At ByteDance, our mission is to inspire creativity and enrich life. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We are passionate about this and hope you are too.​

Job highlights

Yoga and fitness, Stock options, Positive team atmosphere, Career growth opportunity, Paid leave, Flat organization, 100+ mil users, Industry experts, Competitive compensation, Flexible hours

Responsibilities

Team Introduction

Our team develops the core training and serving infrastructure that powers one of the world's largest recommendation systems, enabling billions of personalized recommendations every day. We are also advancing the next generation of AI infrastructure for foundation models and LLMs, driving innovation in large-scale model training, online inference, and GPU optimization.

As part of the team, you will work on distributed training and inference systems, high-performance GPU computing, and scalable LLM infrastructure. You'll collaborate closely with experienced engineers and researchers to transform cutting-edge AI technologies into production systems that directly impact the experience of hundreds of millions of TikTok users. This role is ideal for candidates who are passionate about LLM systems, distributed computing, GPU programming, and building AI systems at massive scale. We are looking for passionate graduates to join our Model Infrastructure team, building the next generation of infrastructure for TikTok's For You recommendation system and Large Language Models (LLMs).

We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth.

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

Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The application limit is applicable to our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities

- Build and optimize infrastructure for large-scale model training and online inference.

- Develop distributed systems supporting large recommendation models and LLMs.

- Improve training and inference performance through GPU optimization and efficient communication.

- Collaborate with researchers to develop and deploy LLM training and serving solutions.

- Analyze system bottlenecks and implement performance optimizations.

Qualifications

Minimum Qualifications:

- Individuals who are completing or have recently completed a Bachelor's degree or above in Artificial Intelligence, Software Development, Computer Science, Computer Engineering or a related discipline.

- Strong programming skills in C++ or Python.

- Good understanding of data structures, algorithms, and computer systems.

- Familiarity with PyTorch or TensorFlow.

- Knowledge of Transformer architectures and Large Language Models (LLMs).

- Strong problem-solving skills and a passion for building large-scale AI systems.

Preferred Qualifications:

- Hands-on experience with LLM training or inference through research, internships, or open-source projects.

- Familiarity with distributed training concepts (e.g., DP, TP, PP, FSDP, ZeRO).

- Experience with GPU programming using CUDA, Triton, or similar technologies.

- Understanding of LLM serving techniques such as KV Cache, Continuous Batching, or FlashAttention.

- Contributions to open-source projects or research in machine learning systems, distributed systems, or LLM infrastructure.