Machine Learning Engineer Intern

About the Role

Global E-Commerce (TikTok Shop) is a fast-growing business and a core revenue driver for TikTok. The Global E-Commerce Content Recommendation team owns the end-to-end recommendation stack for e-commerce video and image-text content globally, including retrieval, ranking, and multi-queue blending; supply ecosystem and cold start; and the browsing-to-purchase experience for hundreds of millions of users. The team is focused on rebuilding the recommendation stack on LLM foundations. This internship offers hands-on experience, industry exposure, and opportunities to apply knowledge to real-world challenges.

Key Responsibilities

• Build and rewrite an industrial recommendation system serving a billion-scale user base across short-video, livestream, and product scenarios, covering retrieval, pre-ranking, ranking, and blending end to end.
• Scale recommendation models like LLMs. Push ranking models from hundreds of millions to billions of parameters and chart the scaling laws of recommendation: behavior-corpus pretraining; multi-scenario, multi-task, multi-stage joint training; ultra-long behavior-sequence modeling (10K+ events) with KV caching, sequence compression, user/generation (U-G) disaggregated serving, speculative decoding, and dynamic batching — raising MFU while holding a strict millisecond latency budget.
• Build one-stage generative retrieval, reframing retrieval as generation by tokenizing the item space into semantic IDs (RQ-VAE / SID) and training autoregressive models, grounded in MLLM semantics, to generate user-desired items.
• Inject world knowledge using large models to mine latent user interests and semantic representations, and use reasoning models for explicit chain-of-thought inference over long-horizon user intent.
• Push training and inference to the hardware limit using custom CUDA / Triton fused kernels, memory and computation-graph optimization, distributed training and inference acceleration, mixed precision, and low-bit quantization.
• Rewrite R&D with agents: automated feature mining and pipeline generation, experiment configuration and training orchestration, automated evaluation and online-diagnosis attribution, bad-case mining and patrol.
• Do original work on open problems such as long-term value modeling, repurchase and retention, transaction attribution, fatigue modeling, new-user recommendation, incremental value modeling, interest exploration, and LLM4Rec. Internal papers, patents, and publication at top external venues are supported.

Requirements & Tech Stack

• Currently pursuing an Undergraduate degree in Software Development, Computer Science, Computer Engineering, or a related discipline.
• Solid ML and engineering fundamentals: understanding of model mathematics, clean and efficient code, strong command of algorithms and data structures.
• Deep research or engineering practice in at least one of: LLMs / foundation models, NLP, CV, RL, or recommendation / search / ads.
• Genuine enthusiasm for LLM / LRM techniques.
• Strong problem definition and decomposition skills.

Preferred Qualifications

• Publications at KDD, SIGIR, RecSys, WWW, ACL, NeurIPS, ICML, ICLR, or comparable venues — or high-quality open-source work.
• CUDA / Triton kernel development, source-level deep-learning-framework optimization, large-scale distributed training, or high-performance inference deployment.
• Hands-on experience with LLM post-training (SFT / RLHF / DPO / GRPO), agent-system construction, or inference acceleration.
• Led or deeply contributed to a key project in search, ads, recommendation, or large models, with a complete problem-to-online-impact loop.
• Awards in ACM-ICPC, NOI, Kaggle, or comparable competitions.
• Heavy user of AI coding and agentic workflows for building systems and optimizing models.

Internship Details

• Hourly Rate: $42.75
• Benefits: Day one access to health insurance, life insurance, wellbeing benefits. 10 paid holidays per year and paid sick time (56 hours if hired in first half of year, 40 if hired in second half of year). Potential eligibility for housing allowance for non-remote interns.
• Program: Offers hands-on experience, industry exposure, and opportunities to apply knowledge to real-world challenges. Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops.
• Application Limit: Candidates may apply to a maximum of two positions globally. Applications are reviewed on a rolling basis. Please clearly state your availability in your resume, including your start and end dates.