Machine Learning Engineer Graduate, Trust And Safety Engineering

Responsibilities About Tik Tok Tik Tok is the leading destination for short-form mobile video.
At Tik Tok, our mission is to inspire creativity and bring joy.
Tik Tok's global headquarters are in Los Angeles and Singapore, and its offices include New York, London, Dublin, Paris, Berlin, Dubai, Jakarta, Seoul, and Tokyo.
Why Join Us Creation is the core of Tik Tok's purpose.
Our products are built to help imaginations thrive.
This is doubly true of the teams that make our innovations possible.
Together, we inspire creativity and enrich life - a mission we aim towards achieving every day.
To us, every challenge, no matter how ambiguous, is an opportunity; to learn, to innovate, and to grow as one team.
Status quo? Never.
Courage? Always.
At Tik Tok, we create together and grow together.
That's how we drive impact-for ourselves, our company, and the users we serve.
Join us.
Team Introduction Building a world where people can safely discover, create and connect.
The Trust & Safety (T&S) team at Tik Tok helps ensure that our global online community is safe and empowered to create and enjoy content across all of our applications.
We have invested heavily in human and machine-based moderation to remove harmful content quickly and often before it reaches our general community.
We are looking for talented individuals to join us in 2026.
As a graduate, you will get unparalleled opportunities for you to kickstart your career, pursue bold ideas and explore limitless growth opportunities.
Co-create a future driven by your inspiration with Tik Tok.
Candidates can apply to a maximum of two positions and will be considered for jobs in the order you apply.
The application limit is applicable to Tik Tok and its affiliates' jobs globally.
Applications will be reviewed on a rolling basis - we encourage you to apply early.
As a Machine Learning Engineer, you'll have the chance to work with our clients and teams to address key business problems and identify areas of growth for the company.
With your education and experience, you will be able to take on real-world challenges from day one.
Responsibilities Work with our world-class engineers to build industry-leading trust and safety systems for Tik Tok Develop and build up highly-scalable classifiers, tools, models and algorithms leveraging cutting-edge machine learning, computer vision and data mining technologies Improve our trust and safety strategy and work on model iterations Collaborate with cross-functional teams to protect Tik Tok globally Qualifications Minimum Qualifications : Currently pursuing your bachelors or completed within 1 year; Computer Science or 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 Preferred Qualifications : Passion about techniques and solving challenging problems Previous experience in applications of machine learning, pattern recognition, NLP, data mining, or computer vision Currently pursuing your Ph D or Master degree in Computer Science or related engineering field.
Tik Tok is committed to creating an inclusive space where employees are valued for their skills, experiences, and unique perspectives.
Our platform connects people from across the globe and so does our workplace.
At Tik Tok, our mission is to inspire creativity and bring joy.
To achieve that goal, we are committed to celebrating our diverse voices and to creating an environment that reflects the many communities we reach.
We are passionate about this and hope you are too.
In the spirit of reconciliation, Tik Tok acknowledges the Traditional Custodians of country throughout Australia and their connections to land, sea and community.
We pay our respect to their Elders past and present and extend that respect to all Aboriginal and Torres Strait Islander peoples today.
By submitting an application for this role, you accept and agree to our global applicant privacy policy, which may be accessed here.
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