Algorithm Engineer

Job Description

Algorithm Engineer | TikTok

The Tone:
This is an early career position at TikTok, located in Los Angeles, CA. TikTok is the leading destination for short-form mobile video, with a mission to inspire creativity and bring joy globally. This role is critical for the Algorithm Team, which protects the platform and its users by developing advanced computer vision, NLP, and multimodality models and algorithms. This ensures the detection and prevention of content and behaviors that violate community guidelines, thereby providing an exceptional and safe user experience for everyone worldwide.

The TL;DR
• Role: Early Career
• Type: Full-time
• Location: In-person, Los Angeles, CA
• Pay: $129960–$246240 yearly
• Team: Algorithm Team
• Mission: Develop and optimize state-of-the-art computer vision, NLP, and multimodality models and algorithms to detect and prevent content and behaviors that violate community guidelines and related regulations, ensuring TikTok provides an exceptional user experience.
• Tech Stack: Computer vision models, NLP models, Multimodality models, Distributed model training frameworks, Unimodal/multimodal content classifiers, Active Learning models, Reinforcement Learning models, Large Language Models

What You’ll Actually Do
• Model Development: Participate in the development of cutting-edge content understanding models to significantly enhance the recognition ability of violated content within TikTok.
• Framework Optimization: Continuously optimize the distributed model training framework to ensure efficiency and scalability for model training.
• Strategic Collaboration: Collaborate with product teams to define business objectives and enhance the overall trust and safety strategy of the platform.
• Deployment & Scalability: Partner with engineering teams to seamlessly deploy machine learning models, design efficient online model workflows, and implement scalable serving pipelines for robust operations.
• Advanced Techniques: Work on state-of-the-art content understanding techniques, including unimodal/multimodal content classifiers, Active Learning models, Reinforcement Learning models, and Large Language Models.

The Must-Haves
• Background: Early career professional holding a Master’s or Bachelor’s degree in Computer Science, Electrical Engineering, Operations Research, Applied Mathematics, or other similar quantitative fields.
• Experience: Possess hands-on or academic experience in at least one of these areas: Machine Learning, Large Language Models, or Recommendation Systems.
• Skills: Strong coding proficiency, demonstrated curiosity towards new technologies, an entrepreneurial mindset, and excellent communication and teamwork abilities.