LLM & Agent Algorithm Intern (Search) - 2027 Start (PhD)

TikTok; Singapore; On-site; SGD 17,000 - 28,000; Full time

Job summary

TikTok is offering a PhD internship in the TT-Search Algorithm & Applied AI team in Singapore. You will contribute to building the search-domain LLM foundation, agent orchestration, memory/self-improvement loops, and evaluation frameworks as part of a dynamic internship program.

Ideal candidates have a PhD candidacy, strong ML/DL grounding, and experience with LLM/Agent projects, PyTorch/TensorFlow, and big data tools. Applications reviewed on rolling basis with early availability preferred.

Qualifications

• PhD candidate in Computer Science or related field.
• Strong ML/DL foundation and familiarity with LLM/Agent technologies.
• Experience with LLM pre-training/fine-tuning/alignment and agent development is preferred.
• Familiarity with PyTorch/TensorFlow for model training and deployment; knowledge of distributed training and inference acceleration.

Responsibilities

• Search LLM Foundation R&D: build and optimize the search-domain LLM foundation and post-training pipelines.
• Agent Engineering & Multi-Agent Orchestration: develop the Harness framework and multi-agent coordination algorithms.
• Long-term memory, self-improvement and RSI: explore memory mechanisms and automated optimization pipelines.
• Evaluation & Reward/Verifier Systems: contribute to online evaluation and annotation-free evaluation systems.
• Business Implementation: work on multimodal AIGC, visual search, on-device intelligence and related tasks.

Skills

ML/DL foundation

LLM/Agent experience

PyTorch/TensorFlow

Big data (MapReduce/Spark)

Education

PhD in Computer Science or related

Tools

PyTorch

TensorFlow

MapReduce/Spark

Job description

Responsibilities

Team Introduction

TT-Search Algorithm & Applied AI is the algorithm team behind the search business built on TikTok (TikTok Search), with the goal of becoming the search engine of choice for users worldwide. Compared with recommendation systems, which passively infer user intent, search delivers content based on users' discovery motivation — making intent expression far more precise. This search data can also feed back into the recommendation engine, helping users obtain more relevant content.

We are at an inflection point where the search paradigm is shifting from "retrieval-and-ranking" toward "Agents proactively completing tasks." With large language models and Agents as our two driving wheels, the team builds the search-domain LLM foundation, the Agent execution framework (Harness), multi-agent collaboration, and self-improvement closed loops. We support the implementation of business scenarios such as multimodal AIGC creation, visual search, on-device intelligence, and long-horizon task Agents — spanning POI search, Wish search, automated evaluation, infrastructure, and more.

We are looking for talented individuals to join us for an internship. PhD internships at Our Company provide students with the opportunity to actively contribute to our products and research, as well as to the organization's future plans and emerging technologies.

Our dynamic internship experience blends hands‑on learning, enriching community‑building and professional development events, and collaboration with industry experts.

Applications will be reviewed on a rolling basis, so we encourage you to apply early. Please clearly state your availability in your resume (Start date, End date).

Responsibilities

• Search LLM Foundation R&D: Build and optimize the search-domain LLM foundation, integrating search knowledge to rapidly deliver business value; develop and refine the post-training pipeline for search LLMs (ultra-long-text / colloquial-text pre-training, image-text / video multimodal representation, e-commerce product multimodal representation learning, etc.); participate in LLM inference optimization (long-context optimization, model efficiency optimization).
• Agent Engineering & Multi-Agent Orchestration (Harness / Loop): Contribute to building the search Agent execution framework (Harness) — unified orchestration of tool calling, planning, memory, and environment interaction; multi-agent cluster scheduling and collaboration algorithms (task allocation, dynamic scheduling, inter-agent communication / alignment / conflict resolution); build the Agent Loop and the "training–inference–evaluation" closed‑loop engineering.
• Long‑term Memory, Self‑Improvement & Data Closed Loop (Self‑Evolve / RSI): Work on long‑term memory mechanisms for LLMs, cross‑context knowledge integration, and related directions; engage in cutting‑edge exploration of self‑evolve / self‑improvement and recursive self‑improvement (RSI) (automated hyperparameter tuning, training pipeline automation, AI‑assisted algorithm design, model iteration closed‑loop); data synthesis and quality control (high‑quality vertical‑domain data synthesis, distribution alignment, synthetic data quality evaluation / filtering / refinement).
• Evaluation & Reward/Verifier Systems: Help build online Reward/Verifier systems and automated evaluation frameworks — annotation‑free automated evaluation; Evaluation of long‑cycle complex tasks and cross‑domain capabilities, and multi‑agent collaboration evaluation standards.
• Business Implementation:Long‑horizon task Agents (persistent intent); Multimodal AIGC creation: leveraging SOTA models for image/video generation to power the Feed's "ask‑after‑viewing / create‑after‑viewing" experiences and strengthen users' proactive mindset; Visual search & on‑device intelligence: object detection, OCR, TinyLLM; Search content / creator ecosystem, etc.

Qualifications

Minimum Qualifications:

• Currently pursuing a PhD's degree, Computer Science or related majors preferred.
• Solid foundation in machine learning / deep learning and familiarity with cutting‑edge LLM and Agent technologies; publications at top‑tier conferences such as NeurIPS / ICML / ICLR / ACL / EMNLP / CVPR / ICCV / ECCV / AAAI, or competition awards, are a plus.
• Experience with LLM / Agent‑related projects is preferred: LLM pre‑training / fine‑tuning / alignment, Agent development (tool calling, planning, memory, multi‑agent collaboration), RAG, RLHF / RLAIF, data synthesis, automated evaluation, etc.
• Familiarity with PyTorch / TensorFlow for model training and deployment; understanding of acceleration methods such as distributed training and mixed‑precision training; knowledge of model compression and inference acceleration (quantization, pruning, distillation, TensorRT, etc.).
• Familiarity with big data frameworks and applications (MapReduce / Spark, etc.) is a plus.

Preferred Qualification

• LLM & Agent: pre‑training / SFT / alignment, long context, Agent Harness and multi‑agent orchestration, data synthesis, self‑improvement (Loop / RSI), automated evaluation;
• CV & Multimodal: image / video retrieval, classification and recognition, image segmentation, object detection, OCR, graph neural networks, multimodal learning, self‑/unsupervised learning; experience with CV / multimodal large‑model projects, or awards in Kaggle / COCO / ImageNet / ActivityNet, are a plus; CVPR / ICCV / ECCV publications preferred;
• NLP: pre‑training, natural language understanding, multilingual / cross‑lingual learning, natural language generation, transfer / semi‑supervised learning; LLM project experience, or awards in GLUE / SuperGLUE / CLUE, are a plus; ACL / EMNLP publications preferred.
• Excellent engineering implementation and learning ability, strong collaboration and communication skills, and genuine passion for search and Agent directions.

Job Information

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.