Responsibilities

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
Creation is the core of TikTok's purpose. Our platform is built to help imaginations thrive. This is doubly true of the teams that make TikTok possible.
Together, we inspire creativity and bring joy - a mission we all believe in and aim towards achieving every day.
To us, every challenge, no matter how difficult, is an opportunity; to learn, to innovate, and to grow as one team. Status quo? Never. Courage? Always.
At TikTok, we create together and grow together. That's how we drive impact - for ourselves, our company, and the communities we serve.
Join us.

About TnS-Live-Algo 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 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.

As a tech lead - machine learning engineer, you will be driving resolution for one or more trust and safety domains, such as recommendation, CV, multimodality, LLM, etc. A successful candidate will have hands-on machine learning and software engineering experience. Also, you will take pride in working with other tech leads, product managers and business partners to identify and solve the most challenging safety and integrity problems in the internet scale.

Responsibilities - What You'II Do
• Build large-scale machine learning models and deploy them to the online trust and safety system
• Develop short-term and long-term machine learning and engineering strategies, define vertical domain's priority and success metrics with our motivated engineers
• Identify tech direction to continuously ship production and improve the ecosystem of our platform
• Collaborate with the product team to define objectives and improve trust and safety strategy
• Collaborate with data analysts to understand and find data patterns

Qualifications

• BS with 5+ years’ industrial experience, or MS/PhD with 3+ years' relevant experience
• Hands on experience in one or more of the following areas: machine learning, deep learning, pattern recognition, anomaly detection, data mining, computer vision, NLP or content understanding
• Experience in trust and safety is a plus
• Good programming skills in Python or similar languages
• Experience in working on large scale production machine learning systems
• Good communication and teamwork skills, passionate about learning new techniques and taking on 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.

Location

Sydney

Job Overview
Job Posted:
3 months ago
Job Expires:
Job Type
Full Time

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