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

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.