TikTok

TikTok

Machine Learning Engineer Intern (E-Commerce Recommendation Video)- 2027 Summer

Seattle, Washington, United States of America · Intern · Internship

Sponsorship not specifiedDetected 27 min ago
ExpressFull-Stack DevelopmentAlgorithmsMachine LearningNLPComputer VisionLLMsResearch

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odds of building a lasting career here

42Risky
Cap-exempt (no lottery)0
Sponsors this role100
Entry-level history0
PERM / green-card track0
Lottery odds40
Fits your clock70

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Employer immigration record

from this employer's Department of Labor filings

Green-card filing pattern in this occupation

Context, not a finding about this posting: of this employer's 106 green-card filings in this occupation, 98% were for a worker who already held the job.

Green-card follow-through: 92%

Of 155 labor certifications old enough to have been used, 12 expired without the employer filing the next step. Median time from filing to decision: 496 days.97% of their filings were for a worker who already held the job.Only certifications past the 180-day window are counted — recent ones cannot have expired yet.

Files H-1B transfers

69 transfer filings in the last year, covering 69 workers. Median labor-condition decision: 7 days. An employer that already files transfers is one that can take over an existing H-1B.

Sourced from Department of Labor LCA, PERM and prevailing-wage disclosure data. Employer matching is by name, so figures may be split across an employer's legal entities. Absence of a filing means none appears in our copy of the data, not that none exists.

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About the role

  • Team Introduction: Global E-Commerce (TikTok Shop) is one of TikTok's fastest-growing businesses and a core driver of the company's revenue growth.
  • We believe recommendation is being rewritten in the compute era.
  • Candidates may apply to a maximum of two positions across Our Company and its affiliates globally.

Responsibilities

  • You will help 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.
  • Build one-stage generative retrieval.
  • We expect, and support, original research: internal papers, patents, and publication at top external venues.
  • Our Global E-Commerce Content Recommendation team owns the end-to-end recommendation stack for e-commerce video and image-text content on TikTok worldwide - retrieval, ranking, and multi-queue blending; supply ecosystem and cold start; and the browsing-to-purchase experience for hundreds of millions of users.
  • Our ambition is to build the most advanced recommendation system in the world, and the next generation after that.

Requirements

  • Deep research or engineering practice in at least one of: LLMs / foundation models, NLP, CV, RL, or recommendation / search / ads - and you can articulate why you made the choices you made, and where they fell short.

Nice to have

  • Publications at KDD, SIGIR, RecSys, WWW, ACL, NeurIPS, ICML, ICLR, or comparable venues - or high-quality open-source work.
  • 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.

Benefits

  • Interns will gain practical experience, explore potential career paths, and participate in social events, learning programs, and development workshops alongside industry professionals.

Company info

  • We are looking for talented individuals to join us for an internship.
  • We are embedding coding agents deep into the algorithm-development loop: automated feature mining and pipeline generation, experiment configuration and training orchestration, automated evaluation and online-diagnosis attribution, bad-case mining and patrol.
  • Our internship program offers students hands-on experience, industry exposure, and opportunities to apply their knowledge to real-world challenges while building a strong foundation for personal and professional growth.

This listing is sourced directly from TikTok's careers page and normalized into a canonical job model.