ML Research Engineer - Global Ads Monetization

TikTok; San Jose (CA); On-site; USD 162,000 - 317,000; Full time

Benefits offered by this job

Medical insurance

Dental insurance

Vision insurance

401(k) with company match

Paid parental leave

Disability coverage

Life insurance

Wellbeing benefits

10 paid holidays per year

Paid sick days per year

Paid Personal Time

Job summary

TikTok is seeking a PhD-level Ads Core ML Engineer to advance a cutting-edge global advertising delivery system. You will work on ML/DL, RL, LLM, and scaling laws to optimize ad ranking, format, and revenue across US markets.

The role focuses on building scalable ML pipelines, improving CTR/CVR, and aligning user experience with advertiser ROI. A strong background in ML frameworks and distributed systems is essential.

Qualifications

• PhD in Computer Science, Software Engineering, or a related field and nearing graduation.
• Proficient in C/C++ and Python with strong data structures knowledge.
• Solid ML/DL knowledge and algorithms fundamentals.
• Experience with TensorFlow, PyTorch, or MXNet and their architectures.

Responsibilities

• Research and develop a cutting-edge global advertising delivery system using ML/DL, RL, LLM, and scaling laws.
• Optimize advertising funnel efficiency across recall, rough-sort, fine-sort (CTR/CVR), and personalization.
• Design system frameworks to improve modeling efficiency.
• Build and manage delivery pipeline for modeling, bidding, traffic strategy, and video recommendation.
• Drive user experience and revenue targets to make the team a core pillar.

Skills

C/C++

Python

ML concepts

Analytical thinking

Critical thinking

Education

PhD in Computer Science/Software Engineering

Tools

TensorFlow

PyTorch

MXNet

Linux

Job description

TikTok is seeking a PhD-level Ads Core ML Engineer to advance a cutting-edge global advertising delivery system. You will work on ML/DL, RL, LLM, and scaling laws to optimize ad ranking, format, and revenue across US markets.

The role focuses on building scalable ML pipelines, improving CTR/CVR, and aligning user experience with advertiser ROI. A strong background in ML frameworks and distributed systems is essential.