Machine Learning Engineer, TikTok Core Feed Recommendation - User Growth

$145,000 - $250,000/Yr

Tiktok - San Jose, CA

Full-time - Entry Level

San Jose, CA

Computing Infrastructure Providers, Data Processing, Web Hosting, and Related Services

About the position

TikTok is the leading destination for short-form mobile video, and our mission is to inspire creativity and bring joy. The TikTok Core Feed Recommendation team plays a crucial role in this mission by designing, implementing, and improving the core recommendation algorithms that power the "for you" and "following" feeds of the TikTok app. This recommendation system connects hundreds of millions of users with relevant content from billions of videos in real-time, fostering high-quality content creation for millions of creators on the platform. The User Growth team, an essential pillar of the Core Feed Recommendation team, is directly responsible for implementing and refining new user acquisition and retention strategies. Our commitment to achieving TikTok's ultimate goals is reflected in our development of high-performance models and sound strategies. We pride ourselves on our rigorous approach to applied research, innovative system design, and steadfast pragmatism. 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 collaborating across disciplines with global teams in pursuit of excellence.

Responsibilities

• Implement machine learning, recommendation, and causal inference algorithms at large scales to optimize and improve new user acquisition efficiency and user retention across the whole user life cycle.
• Work cross-functionally with product managers, data scientists, and product engineers to understand insights, formulate problems, design and refine machine learning algorithms, and further drive the exciting growth of global TikTok users.
• Analyze and pinpoint specific issues affecting user growth across various regions and markets, and utilize algorithmic levers for targeted optimization.
• 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.

Requirements

• Strong programming skills in Python and/or C/C++, and a deep understanding of data structures and algorithms.
• Familiar with the architecture and implementation of at least one mainstream machine learning programming framework (TensorFlow/Pytorch/MXNet).
• Possess keen data insights and clear organization skills, capable of addressing various problems and challenges in growth scenarios.
• Good communication and teamwork skills, be passionate about learning new techniques and taking on challenging problems.

Nice-to-haves

• Minimum of 1 year of 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.
• Prior industry experience with the main components of recommendation systems (retrieval, ranking, re-ranking, cold-start, etc.) is a plus but not required.
• Publications at main conferences such as KDD, NeurIPS, WWW, SIGIR, WSDM, CIKM, ICLR, ICML, IJCAI, AAAI, RecSys or related conferences.
• Strong tracking record of success in data mining, machine learning, or ACM-ICPC/NOI/IOI competitions.
• Participation in public/open-source AI-related projects which are of high visibility.

Benefits

• 100% premium coverage for employee medical insurance, approximately 75% premium coverage for dependents, and a Health Savings Account (HSA) with a company match.
• Dental, Vision, Short/Long term Disability, Basic Life, Voluntary Life and AD&D insurance plans.
• Flexible Spending Account (FSA) Options like Health Care, Limited Purpose and Dependent Care.
• 10 paid holidays per year plus 17 days of Paid Personal Time Off (PPTO) (prorated upon hire and increased by tenure) and 10 paid sick days per year.
• 12 weeks of paid Parental leave and 8 weeks of paid Supplemental Disability.
• Mental and emotional health benefits through our EAP and Lyra.
• 401K company match, gym and cellphone service reimbursements.