Staff Machine Learning Engineer, Content Safety & Ecosystem -- Multimodality

New Yesterday

About the TeamThe Responsible Recommendation System team innovates in content understanding and recommendation system techniques to improve TikTok content safety and ecosystem. We leverage cutting-edge multi-modality modeling to develop robust, scalable solutions that safeguard user experience and drive product impact. The team is dynamic, fast-pacing, collaborative and impact-driven. Responsibilities - Develop a critical content understanding product by leveraging cutting-edge multi-modality models. - Innovate on multi-modality and recommendation system techniques to build end-to-end scalable solutions. - Collaborate with engineers from diverse technical backgrounds and cross-functional teams to integrate advanced modeling techniques into production. - Drive data-driven improvements by conducting rigorous analysis and experiments to address complex ecosystem challenges.
Minimum Qualifications - Bachelor's degree in computer science or a related field, with relevant work experience. - Hands-on experience working on multi-modality models and building robust machine learning infrastructure. - Experience with at least one programming language like C++/Python or equivalent. - Strong statistical background with clear reasoning for conceptualizing and analyzing complicated content safety and ecosystem challenges. - Demonstrated ability in designing scalable machine learning products with a keen product design and abstraction sense. - Excellent communication and teamwork abilities, with a proven track record of collaborating in cross-functional settings.
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Location:
San Jose

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