Machine Learning Engineer Graduate (Ads Signal & Measurement) - 2027 Start
Core
Build and improve machine learning models for signal quality, identity resolution, and attribution to maximize the true business value of ad spend on TikTok.
Role type
Machine Learning Engineer (Graduate)
Builds
Large-scale systems and models for advertising effectiveness, powering downstream ads ranking and delivery.
Domain
Advertising technology, large-scale machine learning, causal inference
Deliverable
production ML models
Required skills
Machine learning, statistics, Python, Go, Java, C/C++, data structures and algorithms, hypothesis testing, regression, probabilistic models, causal inference
Preferred skills
Computational advertising, recommendation/search ranking, causal inference, A/B experimentation, entity resolution, graph learning, anomaly detection, applied LLMs/NLP, large-scale data processing frameworks, ML frameworks
Technologies
Spark, Flink, PyTorch, TensorFlow
Responsibilities
Build ML models for signal quality (anomaly detection, signal recovery, denoising); Contribute to cross-platform identity resolution via probabilistic matching and graph algorithms; Design and implement attribution models (MTA, modeled conversions, incrementality); Drive application of signals in ranking models for conversion prediction and bidding; Build experimentation infrastructure for Conversion Lift and Split Test; Explore LLM-powered signal intelligence; Collaborate with Product, Data Science, and Infrastructure teams.
Seniority
Junior, hands-on IC
