Lead Machine Learning Engineer (Multiple Positions)
TikTok.com
Office
Seattle, Washington, United States
Full Time
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.
About the Team
Our team plays a crucial role in ensuring the company’s success. We seek people who are willing to learn and put in the effort to solve problems. Our challenges are not your regular day-to-day problems - you’ll be part of a team that’s developing new solutions to new challenges. It’s working fast, at scale, and we’re making a difference. We are looking for talents to join us on this exciting journey!
Responsibilities
Analyze user behavior and apply machine learning (ML) algorithms to optimize content consumption and production experience by understanding product objectives and ML techniques to improve model and recommendation strategy.
Design and apply ML algorithm and recommendation strategies to improve users’ experience on platform and content, including videos and livestreams.
Build industry leading recommendation system, and develop highly scalable classifiers and tools leveraging ML.
Build full-stack search engine system and combine information retrieval technology with modern ML methods from related fields such as natural language processing (NLP), Computer Vision (CV), and recommender system.
Work on highly scalable classifiers, predictive models and algorithms in big data mining, CV, NLP, and other domains.
Work with engineering teams to implement model pipeline and deploy services at scale.
Conduct offline and online experiments, analyze data accordingly and evaluate to improve algorithms and strategies.
Work with Data Engineers, Data Analysts, Product and other engineers to deliver features to drive the user growth of products.
Build the core systems and algorithms development including query understanding, result ranking, query recommendation, and system reliability.
Partner with product managers and product strategy and operation team to define product strategy and features.
Collaborate with strategy team, product managers, policy team and other key stakeholders to define products and drive initiatives from engineering viewpoint.
Work with large, complex data sets to solve difficult, non-routine analysis problems by applying advanced analytical methods as needed.
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.
About the Team
Our team plays a crucial role in ensuring the company’s success. We seek people who are willing to learn and put in the effort to solve problems. Our challenges are not your regular day-to-day problems - you’ll be part of a team that’s developing new solutions to new challenges. It’s working fast, at scale, and we’re making a difference. We are looking for talents to join us on this exciting journey!
Responsibilities
Analyze user behavior and apply machine learning (ML) algorithms to optimize content consumption and production experience by understanding product objectives and ML techniques to improve model and recommendation strategy.
Design and apply ML algorithm and recommendation strategies to improve users’ experience on platform and content, including videos and livestreams.
Build industry leading recommendation system, and develop highly scalable classifiers and tools leveraging ML.
Build full-stack search engine system and combine information retrieval technology with modern ML methods from related fields such as natural language processing (NLP), Computer Vision (CV), and recommender system.
Work on highly scalable classifiers, predictive models and algorithms in big data mining, CV, NLP, and other domains.
Work with engineering teams to implement model pipeline and deploy services at scale.
Conduct offline and online experiments, analyze data accordingly and evaluate to improve algorithms and strategies.
Work with Data Engineers, Data Analysts, Product and other engineers to deliver features to drive the user growth of products.
Build the core systems and algorithms development including query understanding, result ranking, query recommendation, and system reliability.
Partner with product managers and product strategy and operation team to define product strategy and features.
Collaborate with strategy team, product managers, policy team and other key stakeholders to define products and drive initiatives from engineering viewpoint.
Work with large, complex data sets to solve difficult, non-routine analysis problems by applying advanced analytical methods as needed.
Lead Machine Learning Engineer (Multiple Positions)
Office
Seattle, Washington, United States
Full Time
August 9, 2025