Research Engineer - Computer Vision, Trust & Safety (Australia)

Sydney, New South Wales, Australia

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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, 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.

About the Team
Our algorithm team is responsible for developing state-of-the-art computer vision and multimodality models and algorithms to protect our platform and users from the content and behaviors that violate community guidelines and related local regulations. With the continuous efforts from our team, TikTok Livestream is able to provide the best user experience and bring joy to everyone in the world.

Job Description
We are looking for a highly self-motivated research engineer to join our algo team in Australia. In our team, you will have the opportunity to participate in the development of the cutting-edge content understanding model to help improve the recognition ability of violated content in TikTok Livestream, and will also be responsible for optimizing our distributed model training framework continuously. The ideal candidate should be experienced in building a computer vision model or multimodality model and have a very strong coding ability in Pytorch/Tensorflow

Responsibilities
- Develop computer vision model or multimodality model to recognize violation content in TikTok Livestream
- Explore cutting-edge multimodal or computer vision large models (CLIP, COCA, ALBEF, BLIP, Flamingo, ViT-G, ViT-22B, EVA-enormous, etc)
- Explore the application of LLM in our business scenarios, like pre-training, zero-shot/ few-shot learning, hard case mining, etc
- Continuously optimize the training framework to better adapt to the training of large models
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* Salary range is an estimate based on our AI, ML, Data Science Salary Index 💰

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Tags: Computer Vision LLMs Model training PyTorch Research TensorFlow

Perks/benefits: Career development

Region: Asia/Pacific
Country: Australia

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