Responsibilities

About the Team

Our Trust and Safety R&D team is fast growing and responsible for building machine learning models and systems to identify and defend internet abuse and fraud on our platform. With the continuous efforts from our team, Tik Tok is able to provide the best user experience and bring joy to everyone in the world.

Our mission is to build a bridge for collaboration between algorithm models and business scenarios, and efficiently and stably apply TnS's algorithmic capabilities to Tik Tok's business scenarios. And let TnS's algorithmic capabilities cover wherever Tik Tok needs them.

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 Tik Tok.

Key Responsibilities

• Work closely with business teams to optimize the integration plan for algorithm applications, improve efficiency in evaluating and using algorithm applications across various business scenarios, and reduce the cost of managing and optimizing algorithm applications in different business scenarios.
• Be responsible for the architectural design, development, and performance tuning of algorithm applications, solving technical challenges such as high concurrency, high reliability, and high scalability. Work includes multiple sub-areas: ML model training and evaluation, model optimization, model inference, model management, dataset management, workflow orchestration, etc.
• Responsible for the design and development of Machine Learning infrastructure for LLM/AIGC, etc
• Be responsible for researching and implementing cutting-edge engineering technologies related to LLM, NLP, CV.

Qualifications

Minimum Qualifications

• Final year or recent graduate with a background in computer science or a related technical discipline.
• Familiar with one or two programming languages, such as C++, Go, or Python, and knowledgeable about CUDA or deep learning frameworks (such as Py Torch, Deepspeed, Megatron, vllm, etc.).
• Understanding of the principles of distributed systems, large-scale data processing, and parallel computing
• Interested and experienced in one or more of the following areas: machine learning, deep learning, computational acceleration, and performance optimization.
• Familiar with the ML Infrastructure of Large Model training and inference

Preferred Qualifications

• Excellent programming skills, data structure and algorithm skills, proficient in C/C++ or Python programming language, candidates with awards in ACM/ICPC, NOI/IOI, Top Coder, Kaggle and other competitions are preferred.
• Research or industry experience in the field of machine learning, especially in large language models (LLMs) and generative artificial intelligence.
• Distributed training framework optimizations such as Deep Speed, FSDP, Megatron, GSPMD
• Experiences in in-depth CUDA programming and performance tuning (cutlass, triton)
• Experience with evaluation of ML models, LLM application & agent development is desirable.
• Understanding cutting-edge LLM research and engineering (e.g., long context, multi modality, active learning, alignment research, agent ecosystem, etc.) and possess practical expertise in effectively implementing these advanced

Additional Information

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 Tik Tok and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early.

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