Software Engineer Graduate

About the Role

The TikTok AI & Visual Search Infrastructure team builds systems that power intelligent search experiences for users worldwide. Our infrastructure handles billions of search requests daily, supporting products like traditional search, AI-powered search results, in-app chatbots, and visual search. We work on foundational search engine infrastructure and the evolving AI Search technology stack, including large-scale indexing and retrieval systems, multimodal search infrastructure, multi-agent and RAG engines, and high-performance LLM/VLM training and serving platforms. As an engineer on this team, you will tackle complex problems across AI Agents, RAG, LLM/VLM inference/training, distributed systems, search engines, and multimodal machine learning. You will collaborate with engineers, researchers, and product teams to shape the future of TikTok Search.

Key Responsibilities

• Design, build, and optimize large-scale infrastructure for TikTok AI Search & Visual Search, supporting billions of online search requests and large-volume offline data processing.
• Evolve TikTok’s search agent platform, including multi-agent orchestration, ReAct and tool-calling workflows, RAG indexing & serving engine, and context/memory management.
• Deploy and optimize LLM/VLM post-training and inference, including GPU inference acceleration, SFT/RL efficiency, kernel/CUDA optimizations, and offline throughput improvement.
• Build and improve search engine components such as offline document processing pipelines, distributed indexing systems for billion/trillion documents, feature extraction services, and multi-stage retrieval/ranking services.
• Develop scalable data pipelines and distributed systems for processing billion- or trillion-scale text, image, and video datasets, covering offline computation, stream processing, task scheduling, storage, and data quality.
• Explore emerging technologies in personalized search, generative search, multimodal understanding, reinforcement learning, model alignment, and evaluation.
• Collaborate with machine learning, product, and other engineering teams to deliver accurate, responsive, and engaging AI-powered and visual search experiences.

Requirements & Tech Stack

• Strong programming skills and a solid foundation in data structures and basic algorithms.
• Familiarity with Linux development environment and proficiency in at least one programming language such as C++, Java, Python, or Go.
• Strong analytical and problem-solving abilities, with an interest in solving complex engineering problems at scale.
• Effective communication and collaboration skills, along with a strong sense of ownership and willingness to learn.

Qualifications

• Individuals who are completing or have recently completed a Bachelor's degree in Computer Science or a related discipline.
• Preferred Qualification(s):
• Internship, research, course project, or open-source experience in one or more of the following areas:
• LLM/VLM serving, RAG, or AI agents
• Distributed systems, storage systems, and large-scale data processing
• Search engines, information retrieval, recommendation systems, or advertising systems
• Understanding of search engine concepts such as query understanding, indexing, retrieval, ranking, and result aggregation.
• Familiarity with LLM serving frameworks such as vLLM, SGLang, or TensorRT-LLM, or agent development frameworks such as LangGraph, is a plus.
• Experience analyzing or optimizing system performance, including latency, throughput, concurrency, memory utilization, or resource efficiency.
• Ability to learn new technologies quickly and apply them to practical engineering or research problems.

Job Information

• 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.
• Applications will be reviewed on a rolling basis.