Machine Learning Engineer Graduate, Trust and Safety Engineering
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About the Role
As a Machine Learning Engineer Graduate at TikTok, you will have the chance to work with world-class engineers to build industry-leading trust and safety systems. Your tasks will include developing classifiers, tools, and algorithms while improving our overall trust and safety strategy. You will also collaborate with cross-functional teams to provide global protection for TikTok users.
About the Candidate
Minimum Qualifications:
- Currently pursuing your bachelor's degree or completed within 1 year in Computer Science or a related field.
- Solid knowledge in at least one area such as machine learning, pattern recognition, NLP, data mining, or computer vision.
- Firm understanding of data structures and algorithms.
- Great communication and teamwork skills.
Preferred Qualifications:
- Passion for problem-solving and technical challenges.
- Previous experience in machine learning and related fields.
- Currently pursuing a Master’s or PhD in Computer Science or a related engineering field.
About TikTok
TikTok is the leading destination for short-form mobile video, dedicated to inspiring creativity and bringing joy to its users. The company has global offices, with headquarters in Los Angeles and Singapore, as well as locations in major cities including New York, London, and Dublin.
Company Culture and Benefits
At TikTok, creation is at the core of our mission. Our culture thrives on challenges and innovation. We emphasize collaboration and support personal growth among team members. TikTok is committed to providing an inclusive environment where every employee's skills, experiences, and unique perspectives are valued.
Commitment to Diversity and Inclusion
TikTok acknowledges the Traditional Custodians of the lands in Australia, paying respect to Elders past and present and extending that respect to all Aboriginal and Torres Strait Islander peoples. We are committed to fostering diversity and celebrating various voices within our community, both on our platform and in our workplace.