Research Scientist Graduate - ML Recommendation Systems

You will be joining our Applied Machine Learning team, a central team responsible for delivering state-of-the-art solutions powering our company's recommendations, ads, and search systems across various products. We own the end-to-end ML lifecycle, from ideation and research to building, deploying, and iterating on models in production. We are looking for candidates who are passionate about solving complex problems and have a strong foundation in machine learning theory and practice. We are looking for a talented and motivated Research Scientist / Algorithm Engineer to join our team, where you will explore the deep integration of recommendation algorithms and large language models (LLMs) / multimodal understanding. We are looking for talented individuals to join our team. As a graduate, you will get opportunities to pursue bold ideas, tackle complex challenges, and unlock limitless growth. Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume. 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 our Company and its affiliates' jobs globally. Applications will be reviewed on a rolling basis - we encourage you to apply early. Responsibilities: - Conduct cutting-edge research on the fusion of recommendation systems and LLMs/multimodal models, with a focus on areas including LLM4Rec, cross-platform and cross-scenario Foundation Models, hundred-billion-parameter scale models, and multimodal large models. - Drive the application and optimization of deep learning algorithms within TikTok products, spanning recommendation, advertising, multimodal understanding, and other compute-intensive domains. - Collaborate closely with engineering teams to explore and validate novel algorithms under new architectures. Minimum Qualifications: - Individuals who are completing or have recently completed a Undergraduate/ Master's degree in Computer Science or a related discipline. - Proven track record of leading high-impact projects or publications in recommendation systems, advertising, or large language model research is a strong plus. - Solid foundations in machine learning and NLP, with strong research and problem-solving capabilities; publications at top-tier venues such as ACL, NeurIPS, ICML, ICLR, or CVPR are highly preferred. - Self-motivated, intellectually curious, and comfortable working in a fast-paced, challenge-driven environment; strong team collaboration and communication skills.