Generative ML Engineer Intern – Recommender Systems

InternHunt; Seattle, Northern (WA, KY); Hybrid; USD 65,000 - 92,000; Full time

Benefits offered by this job

Health insurance

Wellbeing benefits

Paid holidays

Housing allowance

Job summary

TikTok in Seattle is seeking a PhD internship candidate to contribute to our Global E‑Commerce Content Recommendation stack. You will help build and rewrite an industrial recommender serving billions of users, covering retrieval, ranking, and blending end‑to‑end, with production deployment at every iteration.

You will work on LLM‑based retrieval, large‑scale model scaling, and agent‑driven research, gaining hands‑on experience in cutting‑edge systems and bringing ideas from theory to production

Qualifications

• Pursuing a PhD in CS, EE, math, statistics or related discipline.
• Strong ML and engineering fundamentals with clean, reproducible code.
• Experience in LLMs / NLP / CV / RL / or recommendation / search / ads; able to justify choices.
• Genuine enthusiasm for LLM/LRM techniques and production-ready mindset.
• Strong problem definition and decomposition when facing ambiguous problems.

Responsibilities

• Help build and rewrite an industrial recommender for a billion-scale user base.
• Work on retrieval, ranking, and blending end-to-end with production deployments.
• Contribute to scalable model development, training and inference acceleration.

Skills

ML fundamentals

Algorithms & data structures

Clean code

Research mindset

Education

PhD in Computer Science, Electrical Engineering, Math, Statistics or related

Tools

CUDA / Triton kernels

DL frameworks

Job description

TikTok in Seattle is seeking a PhD internship candidate to contribute to our Global E‑Commerce Content Recommendation stack. You will help build and rewrite an industrial recommender serving billions of users, covering retrieval, ranking, and blending end‑to‑end, with production deployment at every iteration.

You will work on LLM‑based retrieval, large‑scale model scaling, and agent‑driven research, gaining hands‑on experience in cutting‑edge systems and bringing ideas from theory to production