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.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is 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 bring joy - a mission we work towards every day.

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. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. 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

TikTok 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 TikTok, our mission is to inspire creativity and bring joy. 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

About the Team

The Recommendation Architecture team is responsible for building up and optimizing our recommendation system's architecture to provide the most stable and best experience for our users. As a New Graduate, you'll join a high-impact team focused on optimizing Large Language Models (LLMs) and large-scale recommender models optimization on GPU platforms. You'll build and scale AI infrastructure that powers state-of-the-art models in production.

We are looking for talented individuals to join our team in 2026. 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 TikTok.

Successful candidates must be able to commit to an onboarding date by end of year 2026. 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 TikTok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

Responsibilities

- Optimize model performance and memory efficiency on GPU-based systems.

- Collaborate with research and infra teams to deploy high-throughput training and inference pipelines.

- Develop tools and libraries to accelerate deep learning workloads at scale.

- Analyze system performance (e.g., GPU profiling, kernel analysis, throughput tuning).

Qualifications

Minimum Qualifications:

- Final year or recent graduate with a a background in Computer Science, Electrical Engineering, or other related field.

- Solid programming skills in C++/CUDA/Trition/Python.

- Familiarity with GPU architecture and distributed training is highly desirable.

Preferred Qualifications:

- Experience building production-grade training and inference systems for large-scale models.

- Hands-on experience optimizing Large Language Models (LLMs), including memory efficiency, latency, and throughput improvements.

- Knowledge of distributed training frameworks (e.g., NCCL, Horovod, DeepSpeed, FSDP) is a plus.

- Familiarity with deep learning compiler frameworks such as TVM or LLVM, and understanding of their underlying principles.

- Contributions to open-source projects or relevant research publications.

By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

If you have any questions, please reach out to us at apac-earlycareers@tiktok.com