Graduate Backend Engineer: Multimodal AI Infra in Sydney

At TikTok, the Media Platform Team builds the multimedia infrastructure powering TikTok and other products. As part of the VideoArch department, we are evolving beyond traditional video processing to build industry-leading multimedia AI computing platforms that power next-generation AI applications. Our team develops large-scale multimodal data processing and AI computing platforms that support foundation model pre-training pipelines across vision, language, and generative AI workloads, as well as real-time AI communication services.

We also build high-performance distributed computing infrastructure, intelligent scheduling systems, and cloud-native resource management platforms that efficiently orchestrate massive GPU and CPU clusters. In addition to advancing AI infrastructure, we continue to optimize TikTok's world-class Video-on-Demand (VoD) processing platform, which processes billions of videos every day and delivers reliable, cost-efficient multimedia services at global scale.

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. 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 the next-generation multimedia AI computing platform that powers multimodal data processing for foundation model training, as well as real-time AI applications.
• Design and develop high-performance distributed infrastructure, including data processing frameworks, workflow orchestration, task scheduling, resource management, model and operator management, and autoscaling.
• Build cloud-native systems on Kubernetes and optimize the orchestration and scheduling of heterogeneous GPU and CPU clusters for large-scale AI workloads.
• Continuously improve the scalability, reliability, performance, and cost efficiency of TikTok's multimedia processing infrastructure supporting billions of videos every day.

Qualifications:

Minimum Qualification(s):

• Individuals who are completing or have recently completed a Bachelor's/Masters' degree in Software Development, Computer Science, Computer Engineering, or a related technical discipline.
• Solid basic knowledge of computer software, understanding of Linux operating system, storage, network IO, and other related principles.
• Familiarity with one or more programming languages, such as Go, Python, and C++, with knowledge of design patterns and coding principles.
• Strong learning and research abilities, good communication skills and teamwork spirit.

Preferred Qualification(s):

• Experience in building large-scale infrastructure, distributed systems, or cloud-native platforms.
• Familiarity with AI infrastructure, distributed data processing frameworks, or large-scale computing systems (e.g., Ray, Daft).
• Understanding of large language models (LLMs), multimodal models, and modern AI inference frameworks (e.g., vLLM, SGLang).

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