About the job
Our 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 looking for strong machine learning engineers who are excited to grow their 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 sophisticated Research Engineers who are experienced in machine learning, which can help us create an ecosystem that rewards high quality user experience and advertiser value.
Responsibilities
Drive cutting-edge research in Generative AI and foundation models, leading projects in text generation/translation, multimodal understanding (image/video-to-text), deepfake synthesis/detection, and efficient training/inference for AIGC models. Define technical roadmaps and align with long-term business goals.
Architect and deploy AIGC solutions for monetization ecosystems (ads, e-commerce, short video, live streaming), translating research into scalable systems with measurable business impact.
Engage and lead a high-performing team of researchers/engineers, fostering innovation in large-scale model development, content understanding, and AI-driven productization.
Spearhead cross-functional collaborations with product, engineering, and infrastructure teams to productionize models, ensuring robustness, efficiency, and ethical AI practices.
Shape industry-leading research through patents, publications, and open-source contributions, while maintaining a pulse on emerging trends to guide strategic investments.
Qualifications
Minimum
PhD or MS in Computer Science, Electrical Engineering, or related fields with 5+ years of industry research experience (or equivalent)
Deep expertise in AIGC algorithms (LLMs, diffusion models, etc.), with a proven track record of scaling models from research to production
Strong background in either NLP (text generation, RLHF) or multimodal learning (vision-language models)
Proficiency in PyTorch/JAX, distributed training, and inference optimization (e.g., quantization, model compression)
Team engagement experience, with the ability to mentor and collaborate with cross-functional team stakeholders, set technical direction, and align projects with business objectives
Demonstrated ability to design long-term roadmaps, anticipate industry shifts, and make high-impact technical decisions under fast-paced global business settings.
Preferred
Experience with AI safety, alignment, or adversarial robustness in generative models
Familiarity with reinforcement learning for autonomous agents or large-scale recommender systems