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Machine Learning Engineer - Trust and Safety, NLP (Australia)

Mid levelFull-timeHybridSydney NSW, AustraliaPosted 9 months agoVerified 1 week ago
Pending fitX of Y criteria met

About the job

This job is about building a safer online community at TikTok through innovative Trust & Safety initiatives. By designing and deploying advanced machine learning models, you will play a crucial role in ensuring that users can discover, create, and connect safely. The team thrives on collaboration, creativity, and a shared passion for tackling challenging problems together.

You'll be responsible for

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Building content safety systems

Building industry-leading content safety systems for TikTok to ensure a safe user experience.
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Developing classifiers and algorithms

Developing highly-scalable classifiers, tools, models, and algorithms leveraging cutting-edge machine learning, computer vision, and data mining technologies.
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Collaborating with cross-functional teams

Working with cross-functional teams to protect TikTok globally and improve trust and safety strategies.

Key criteria

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3+ years in machine learning or related fields

Demonstrated experience in machine learning, deep learning, or computer vision.

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Proficiency in deep learning frameworks

Experience with frameworks like PyTorch and TensorFlow for model development.

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πŸ’»

Strong programming skills in Python

Solid understanding of data structures and algorithms for effective coding.

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Meet the team

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5 criteria for this job
3+ years in machine learning or related fields
Demonstrated experience in machine learning, deep learning, or computer vision.

View

Proficiency in deep learning frameworks
Experience with frameworks like PyTorch and TensorFlow for model development.

View

Strong programming skills in Python
Solid understanding of data structures and algorithms for effective coding.

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Published research in AI conferences
Experience publishing in top AI journals or conferences is a valuable asset.

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Good communication and teamwork skills
Ability to collaborate effectively with cross-functional teams.

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A meaningful career starts with a match

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