Graduate Research Scientist - Recommender Systems

TikTok Inc.; San Jose (CA); On-site; USD 162,000 - 388,000; Full time

Benefits offered by this job

Medical, dental, and vision insurance

401(k) with company match

Parental leave

Disability coverage

Life insurance

Wellbeing benefits

Paid holidays / sick days / PTO

Job summary

TikTok Inc. is seeking a Machine Learning Scientist to join the Recommendation team, focusing on building large-scale recommender systems that power personalized content discovery and user experiences.

You will develop cutting-edge models to optimize accuracy, engagement, and scalability across billions of users. The role emphasizes applying deep learning techniques and large-scale systems engineering, collaborating with infrastructure, product, and research teams to solve complex

Qualifications

• PhD in Computer Science, ML, AI, Statistics or related field.
• Experience in recommender systems, ML, CV, or NLP.
• Proficiency in programming, solid data structures and algorithms.
• Familiarity with deep learning architectures such as transformers, CNNs, RNNs, LSTMs.
• Analytical and collaborative problem‑solving skills.

Responsibilities

• Research and develop large-scale recommender systems for personalized, engaging user experiences, focusing on scalability, accuracy, and performance.
• Apply advanced ML and deep learning techniques to optimize TikTok's recommendation algorithms.
• Manage end-to-end lifecycle of recommender models: training, fine‑tuning, deployment, monitoring, and improvement.
• Analyze complex data to uncover user preferences, behaviors, and trends for personalization.
• Collaborate with cross‑functional teams to design innovative solutions that improve relevance and diversity of TikTok recommendations.

Skills

PhD in CS/ML

Recommender systems

Deep learning

Transformers

Programming

Algorithms

Education

PhD in Computer Science or related field

Tools

Python

TensorFlow / PyTorch

Distributed systems

Job description

TikTok Inc. is seeking a Machine Learning Scientist to join the Recommendation team, focusing on building large-scale recommender systems that power personalized content discovery and user experiences.

You will develop cutting-edge models to optimize accuracy, engagement, and scalability across billions of users. The role emphasizes applying deep learning techniques and large-scale systems engineering, collaborating with infrastructure, product, and research teams to solve complex