Graduate Machine Learning Engineer (Trust & Safety)

AI Job Summary

TikTok is the leading destination for short-form mobile video. Our mission is to inspire creativity and bring joy. TikTok has global offices including Los Angeles, New York, London, Paris, Berlin, Dubai, Mumbai, Singapore, Jakarta, Seoul and Tokyo.


Why Join Us

At TikTok, our people are humble, intelligent, compassionate and creative. We create to inspire - for you, for us, and for more than 1 billion users on our platform. We lead with curiosity and aim for the highest, never shying away from taking calculated risks and embracing ambiguity as it comes. Here, the opportunities are limitless for those who dare to pursue bold ideas that exist just beyond the boundary of possibility. Join us and make impact happen with a career at TikTok.


Our Trust and Safety engineering team is responsible for developing state-of-the-art machine learning models and algorithms to protect our platform and users from bad content and abusive behaviors. With the continuous efforts from our trust and safety team, TikTok is able to provide the best user experience and bring joy to everyone in the world.


We are looking for talented individuals to join us in 2024. 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 TikTok.


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 TikTok 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 TikTok

- 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 TikTok globally

Qualifications

- Currently pursuing your PhD or Master degree in 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

- Well understanding of data structures and algorithms

- Great communication and teamwork skills

- Passion about techniques and solving challenging problems


TikTok 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 TikTok, 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, TikTok 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: https://careers.tiktok.com/legal/privacy.


If you have any questions, please reach out to us at [email protected].

Closed 7 hours ago
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Closed 7 hours ago
  • Job type:Graduate Jobs
  • Disciplines:
    Computer Science, Engineering, Engineering Software, Information
    ...
  • Work rights:
    Australian Citizen, Australian Permanent Resident,
    ...
  • Locations:
    Sydney
  • Closing Date:30th Apr 2024, 3:59 pm

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