Foundation Model, Research Engineer Graduate (Monetization Technology – Ads Integrity) – 2026 Start (PhD)

Responsibilities

TikTok Ads Business Integrity team has a strong user focus and a dedication to technical excellence. We aim to meet our users’ needs with reliable and high-performing platforms and services. We are excited to grow our advertisers’ and users’ business understanding, build highly scalable machine learning models, and partner across disciplines with global teams, in pursuit of excellence. Given the fast growth of TikTok in the world, we are working on building a next-generation content understanding system for TikTok monetization. We are seeking an Engineering Manager experienced in machine learning, which can help us create an ecosystem that rewards high quality user experience and advertiser value. Being part of the team, you will: 1. Work on cutting-edge AI research with real-world impact in a fast-growing tech ecosystem. 2. Collaborate with world-class researchers and engineers to push the boundaries of generative AI. 3. Have great access to competitive compensation, trending AI/ML projects, flexible work culture, and opportunities for rapid career growth. We are looking for talented individuals to join our team in 2026. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Launch your career where inspiration is infinite at TikTok. Applications will be reviewed on a rolling basis – we encourage you to apply early. Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply. The Application limit is applicable to TikTok and its affiliates’ jobs globally. Applications will be reviewed on a rolling basis – we encourage you to apply early. Responsibilities: 1. Lead research and development of advanced generative AI technologies, including LLMs, multimodal models (text/image/video), and deepfake detection/synthesis, focusing on optimizing performance across pre-training, SFT, RLHF, and AI safety. 2. Design and deploy cutting-edge AIGC solutions for content understanding and monetization in diverse applications such as ads, e-commerce, short video, and live streaming, contributing to the creation of next-generation AI-driven ecosystems. 3. Drive advancements in LLM-based agents using reinforcement learning to enable autonomous reasoning, planning, and interactive capabilities, addressing real-world challenges in dynamic environments. 4. Innovate techniques to improve the efficiency of large-scale model training and inference, including distillation, quantization, and speculative decoding, for scalable and practical deployment in production. 5. Collaborate with interdisciplinary teams to transition research breakthroughs into production-grade AI services, ensuring robust, low-latency, and cost-effective solutions. 6. Stay at the forefront of generative AI research by contributing to patents, publications, and open-source projects, while actively monitoring and contributing to the latest industry trends and innovations.

Qualifications

Minimum Qualifications: 1. Final year Ph.D or recent Ph.D graduates in Computer Science, AI, Machine Learning, or related fields by 2026 (or equivalent industry experience). 2. Strong foundational experience in deep learning, NLP, and generative models (LLMs, diffusion models, etc.). 3. Hands-on experience with large-scale model training, RLHF (Reinforcement Learning from Human Feedback), and multimodal learning (text, image, video). 4. Proficiency in one or more deep learning frameworks such as PyTorch, JAX, or TensorFlow, with familiarity in distributed training frameworks. Preferred Qualifications: 1. A track record of publications or active research/paper review at top-tier conferences (NeurIPS, ICML, ACL, CVPR, etc.) or equivalent. 2. Knowledge of AI safety, alignment, and adversarial robustness, with an interest in responsible AI development. 3. Experience in developing agentic systems utilizing reinforcement learning. 4. Strong engineering skills with the ability to deploy models at scale and optimize for performance. By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here: https://careers.tiktok.com/legal/privacy

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