Machine Learning Engineer (LLM & Personalized Search), TikTok Search

About TikTok

TikTok is the leading destination for short-form mobile video. At TikTok, our mission is to inspire creativity and bring joy. TikTok's global headquarters are in Los Angeles and Singapore, and we also have offices in New York City, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.

Why Join Us

Inspiring creativity is at the core of TikTok's mission. Our innovative product is built to help people authentically express themselves, discover and connect – and our global, diverse teams make that possible. Together, we create value for our communities, inspire creativity and bring joy - a mission we work towards every day.

We strive to do great things with great people. We lead with curiosity, humility, and a desire to make impact in a rapidly growing tech company. Every challenge is an opportunity to learn and innovate as one team. We're resilient and embrace challenges as they come. By constantly iterating and fostering an "Always Day 1" mindset, we achieve meaningful breakthroughs for ourselves, our company, and our users. When we create and grow together, the possibilities are limitless. Join us.

Diversity & Inclusion

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 are passionate about this and hope you are too.

About the team

Our Search Team is responsible for building and owning TikTok's search engine which provides our users the best search experience. On the TikTok Search Team, you’ll have the opportunity to build a full-stack search engine system and combine information retrieval technology with modern machine learning methods from related fields such as NLP, Computer Vision, Multimodal, and Recommender Systems. We embrace a culture of self-direction, intellectual curiosity, openness, and problem-solving.

Job Responsibilities

Be responsible for the personalization direction of photo-text search, lead the construction and implementation of the personalized algorithm system for photo-text search. Combine the core characteristics of the photo-text genre, focus on improving information acquisition efficiency and tapping the value of interactive comments, rely on large model technology to realize model scaling up and generative recommendation innovation, break through technical bottlenecks, expand the contribution of photo-text search to the search business, and create a user-centric search experience.

1. Be responsible for the implementation of personalized algorithms for photo-text search. Integrate photo-text visual, text and user behavior data to build scenario-adaptable personalized retrieval; rely on large model technology to promote model scaling up, optimize model performance and generalization ability, and explore the application of generative recommendation in photo-text scenarios to accurately match users' potential needs.

2. Focus on photo-text information acquisition efficiency. According to its characteristics of "visual priority, high information density and fragmented reading", reflect the differentiated value of photo-text and solve problems such as user interest mining through the personalized link.

3. Promote model iteration and effect review, collaborate with cross-departmental teams to decompose business objectives into algorithm strategies, drive photo-text search product innovation, and increase the contribution of photo-text in the overall search business.

4. Be responsible for the stability, performance optimization and cost control of the algorithm personalization link, promote full-link monitoring of the algorithm, improve response efficiency, and cooperate with the architecture team to enhance the training and inference efficiency of the personalization link to ensure stability and scalability.

Minimum Qualifications

1. Bachelor's degree or above in a computer-related major, with excellent coding ability and a solid foundation in data structures and algorithms.

2. Familiar with and proficient in programming languages such as C++/Python, and familiar with common data structures and programming algorithms.

3. Solid foundation in machine learning and coding ability, with in-depth research experience in machine learning, NLP, CV, etc., and proficient in major algorithms and data structures.

4. Strong algorithm design and excellent ability to analyze and solve problems, passionate about solving challenging problems, good initiative and curiosity, and good communication and collaboration skills.

Preferred Qualification

1. Experienced in recommendation systems, advertising, search engines and other related fields; priority is given to candidates with R&D or implementation experience in model scaling up and generative recommendation; strong technical innovation and problem-solving abilities; strong business sensitivity and data thinking, able to identify optimization directions through data analysis, and possess good review and iteration abilities.