TikTok is the leading destination for short-form mobile video and our mission is to inspire creativity and bring joy. TikTok is one of the fastest growing apps in the world, and we’re looking for machine learning research scientists and engineers to join our TikTok Core Feed Recommendation team to support that growth and help us empower creators, connect people, and explore possibilities.
TikTok Core Feed Recommendation team sits in the center of TikTok, designs, implements and improves the core recommendation algorithm that powers the "for you" feed, "following" feed, etc. of the TikTok app. The recommendation system we built connects hundreds of millions of users with relevant content out of billions of videos in real-time, and inspires high-quality content creation for millions of creators on the platform.
The team is at the intersection of cutting-edge machine learning research and large-scale end-to-end production systems. We take pride in finding the right balance between solid applied research, elegant system design and being pragmatic. We have a strong user focus and a dedication to technical excellence.
We are looking for strong research scientists and engineers at all levels, who are excited about growing their business understanding, building highly scalable and reliable software, and partnering across disciplines with global teams, in pursuit of excellence.
What you'll do:
– Improve recommendation models at massive scales, through applying state-of-art machine learning techniques across all ranking phases including but not limited to retrieval, ranking, re-ranking and etc.
– Conduct cutting-edge application-driven research to explore the frontier of recommendation algorithmic domain. Develop industry leading recommendation system.
– Work cross functionally with product managers, data scientists and product engineers to understand insights, formulate problems, design and refine machine learning algorithms, and communicate results to peers and leaders.
– Run regular A/B tests, perform analysis and iterate algorithms accordingly.
– Have a good understanding of end-to-end machine learning systems. Work with infra teams on improving efficiency and stability.
‘ Hands-on experience in one or more of the areas: recommender systems, machine learning, deep learning, pattern recognition, data mining, computer vision, NLP, content understanding or multimodal machine learning
‘ Strong programming skills in Python and/or C/C++, and a deep understanding of data structures and algorithms
‘ Familiar with architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/PyTorch/MXNet)
‘ Good communication and teamwork skills, be passionate about learning new techniques and taking on challenging problems
‘ Prior industry experience with main components of recommendation systems(retrieval, ranking, re-ranking, cold-start etc.) is a plus but not required
1. Publications at main conferences such as KDD?NeurIPS?WWW?SIGIR?WSDM?CIKM?ICLR?ICML?IJCAI?AAAI?RecSys or related conferences
2. Strong tracking record of success in data mining, machine learning, or ACM-ICPC/NOI/IOI competitions
3. Participation in public/open-source AI-related projects which are of high visibility
TikTok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives. Our platform connects people from across the globe and so does our workplace. At TikTok, our mission is to inspire creativity and bring joy. To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach. We believe individuals shouldn't be disadvantaged because of their background or identity, but instead should be considered based on their strengths and experience. We are passionate about this and hope you are too.
TikTok is committed to providing reasonable accommodations during our recruitment process. If you need assistance or an accommodation, please reach out to us at [email protected]