13 hours ago

Research Scientist Intern (Monetization GenAI) - 2026 Start (PhD)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Work on TikTok’s Generative AI team within Monetization Technology, advancing large language model and multimodality generative model architectures. Research, implement, and evaluate novel machine learning algorithms, then collaborate with applied machine learning and infrastructure teams to ship new generative models into ad production. This 2026 PhD internship offers hands-on research impact across text, images, videos, and landing-page experiences for advertisers, agencies, and creators.

Location: San Jose

Workplace: Onsite

Employment Type: Internship

Job Function: Data Science & Machine Learning

Seniority: Intern level

Key Responsibilities

•Advance large language model and multimodality generative model architectures through research.
•Research, implement, and evaluate novel machine learning algorithms on generative models.
•Collaborate with applied machine learning and infrastructure teams to ship new generative models into ad production.

Key Requirements

•Currently pursuing a PhD in computer science, machine learning, or similar fields.
•Hands-on experience developing multimodality foundation models (or relevant work/internship experience in an AI research organization).
•Strong publications record in top conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR).
•Experience with large language model or multimodality generative model architectures.
•Research, implementation, and evaluation experience with generative-model machine learning algorithms.

Experience:AI researchGenerative AIMachine learning

Education:PhD / Doctorate in computer science, machine learning

Skills:ResearchCollaborationTechnical evaluation

Tech Stack:Large language modelsMultimodalityGenerative modelsMachine learning

Company Brief

TikTok

Short-form video platform that lets users create, share, and discover entertainment content through algorithmic recommendations. It also offers advertising and creator tools for brands, influencers, and businesses.

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn

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TikTok

13 hours ago

Research Scientist Intern (Monetization GenAI) - 2026 Start (PhD)

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 13 hours agoStatus: Live

Job Summary

Location: San Jose

Workplace: Onsite

Employment Type: Internship

Job Function: Data Science & Machine Learning

Seniority: Intern level

Key Responsibilities

•Advance large language model and multimodality generative model architectures through research.
•Research, implement, and evaluate novel machine learning algorithms on generative models.
•Collaborate with applied machine learning and infrastructure teams to ship new generative models into ad production.

Key Requirements

•Currently pursuing a PhD in computer science, machine learning, or similar fields.
•Hands-on experience developing multimodality foundation models (or relevant work/internship experience in an AI research organization).
•Strong publications record in top conferences or journals (e.g., NeurIPS, ICML, ICLR, CVPR).
•Experience with large language model or multimodality generative model architectures.
•Research, implementation, and evaluation experience with generative-model machine learning algorithms.

Experience:AI researchGenerative AIMachine learning

Education:PhD / Doctorate in computer science, machine learning

Skills:ResearchCollaborationTechnical evaluation

Tech Stack:Large language modelsMultimodalityGenerative modelsMachine learning

Company Brief

TikTok

Industry: Digital Media

Company Size: Enterprise (1,001+ employees)

Growth: Scaleup

Headquarters: Singapore, Singapore

Founded: 2016

Website LinkedIn