ML Engineer: Multimodal & LLM-Driven Recommendations

TikTok; San Jose, Northern (CA, KY); Hybrid; USD 128,000 - 317,000; Full time

Benefits offered by this job

Medical, dental, vision insurance

401(k) with company match

Paid parental leave

Job summary

TikTok in San Jose, CA, is seeking a highly capable candidate to advance our Recommendation Foundation Models. You will contribute across pre-training to post-training, designing multimodal tokenizers and integrating recommendation tasks into LLM training to push state-of-the-art performance.

You will work with cutting-edge multimodal content and scalable architectures. The role emphasizes strong ML/DL fundamentals, proficiency in Python, and a research-driven mindset, with opportunities to

Qualifications

• Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics or related discipline.
• Solid foundation in machine learning and deep learning, with strong interest in LLMs and generative recommendation.
• Proficiency in Python and experience with deep learning frameworks such as PyTorch.
• Self-driven, with a strong research mindset and solid engineering skills.

Responsibilities

• Participate in the full training lifecycle of Recommendation Foundation Models, including pre-training, mid-training, and post-training.
• Design and train multimodal semantic tokenizers for recommendation items, leveraging multimodal foundation models to encode rich item content into discrete semantic tokens and raise the performance ceiling of Recommendation Foundation Models.
• Develop LLM-native recommendation by incorporating recommendation tasks directly into large language model training and leveraging world knowledge to improve recommendation quality.
• Build the next generation of recommendation systems powered by Recommendation Foundation Models, spanning retrieval, ranking, and end-to-end generative recommendation.

Skills

Python

PyTorch

Machine Learning

LLMs

Research mindset

Education

Bachelor's degree in CS/EE/Math/Stats

Job description

TikTok in San Jose, CA, is seeking a highly capable candidate to advance our Recommendation Foundation Models. You will contribute across pre-training to post-training, designing multimodal tokenizers and integrating recommendation tasks into LLM training to push state-of-the-art performance.

You will work with cutting-edge multimodal content and scalable architectures. The role emphasizes strong ML/DL fundamentals, proficiency in Python, and a research-driven mindset, with opportunities to