Machine Learning Engineer Graduate (Trust and Safety Engineering)

About This Role

This graduate role is for a Machine Learning Engineer to join the Trust & Safety team, working to ensure the global online community is safe across the company's applications. The role involves addressing key business problems, identifying growth areas, and contributing to industry-leading trust and safety systems.

Responsibilities

• Collaborate on research projects within the team or across countries
• Work with world-class engineers to build industry-leading trust and safety systems for TikTok
• Develop and build highly-scalable classifiers, tools, models, and algorithms leveraging cutting-edge machine learning, computer vision, and data mining technologies
• Improve the trust and safety strategy and work on model iterations
• Collaborate with cross-functional teams to protect TikTok globally
• Present research outcomes to internal and/or external audiences
• Work with engineering teams to apply technical achievements from research to product prototyping
• Develop and implement innovative machine learning algorithms to manage business risks in TikTok's products and platforms
• Prototype and explore novel solutions, conduct experiments to validate hypotheses, and provide insights to Product and Tech teams

Requirements

• Currently pursuing a PhD or Master's degree in Computer Science or a related engineering field
• Solid knowledge in at least one of the following areas: machine learning, pattern recognition, NLP, data mining, or computer vision
• Firm understanding of data structures and algorithms
• Great communication and teamwork skills

Nice to have:

• Passion about techniques and solving challenging problems
• Previous experience in applications of machine learning, pattern recognition, NLP, data mining, or computer vision

Important Details

• Start date: by end of year 2027

About the Company

The Trust & Safety team at TikTok helps ensure that its global online community is safe and empowered to create and enjoy content across all of its applications. The company has invested heavily in human and machine-based moderation to remove harmful content quickly.