ML Engineer, Trust & Safety Systems

CSEA

Sydney

Hybrid

AUD 70,000 - 90,000

Full time

14 days+

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Job summary

TikTok is seeking a talented graduate Machine Learning Engineer to join our Trust & Safety team in Sydney. You'll tackle real-world problems, build scalable classifiers and ML models, and collaborate with engineers to protect our global community from harmful content.

Success requires a recent degree in computer science or engineering, practical knowledge of ML, data mining, NLP or computer vision, and strong communication skills to work across cross-functional teams in a fast-paced environment.

Qualifications

  • Must have a degree in a technical field such as Software Development, Computer Science or Computer Engineering.
  • Solid knowledge in machine learning, pattern recognition, NLP, data mining or computer vision.
  • Firm understanding of data structures and algorithms; strong communication and teamwork skills.

Responsibilities

  • Work with world-class engineers to build trust and safety systems for TikTok.
  • Develop scalable classifiers, tools, models and algorithms using ML, CV and data mining.
  • Improve trust and safety strategy and iterate models.
  • Collaborate with cross-functional teams to protect TikTok globally.

Skills

Machine learning
Data mining
Computer vision
NLP
Data structures and algorithms
Communication and teamwork

Education

Bachelor's/Master's degree in Software Development
Bachelor's/Master's degree in Computer Science
Bachelor's/Master's degree in Computer Engineering

Job description

TikTok is seeking a talented graduate Machine Learning Engineer to join our Trust & Safety team in Sydney. You'll tackle real-world problems, build scalable classifiers and ML models, and collaborate with engineers to protect our global community from harmful content.

Success requires a recent degree in computer science or engineering, practical knowledge of ML, data mining, NLP or computer vision, and strong communication skills to work across cross-functional teams in a fast-paced environment.

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