AI-Driven Ad Algorithms Engineer

Beijing Foreign Enterprise Management Consultants Co.,Ltd.; Singapore; On-site; SGD 120,000 - 170,000; Full time

Job summary

Huawei is seeking an Advertising AI Algorithm Engineer to join our team in Singapore. You will develop core AI capabilities for the advertising system, including infrastructure, models, and predictive components to improve ad relevance and ROI.

You will research AI technologies such as NLP, LLM, computer vision, andGenerative AI to interpret and generate ad creatives, while working with cross-functional teams on iterative improvements via A/B testing.

Qualifications

• PhD or Master’s in CS, data science, math, or related fields.
• Strong foundation in data structures and algorithms with ML/DL, NLP/LLM, or related areas.
• Proficient in Python/Java/C++/SQL with deep learning frameworks (TensorFlow or PyTorch).
• 1–3 years of research or industry experience in advertising, recommendation systems, generative AI, or related areas.

Responsibilities

• Develop core capabilities for the advertising system, including AI infrastructure and algorithms.
• Analyze data to uncover user interests and improve ad prediction accuracy.
• Design and optimize ad bidding mechanisms and monetization strategies.
• Research AI technologies (NLP, LLM, CV, Generative AI) to enhance ad creatives and experiences.
• Collaborate with product and operations teams to iterate algorithms via A/B testing.

Skills

AI Algorithms

ML/DL

NLP/LLM

Big Data

Distributed Computing

Python

PyTorch/TensorFlow

Education

PhD or Master’s in CS/Math

Tools

TensorFlow

PyTorch

SQL

Job description

Huawei is seeking an Advertising AI Algorithm Engineer to join our team in Singapore. You will develop core AI capabilities for the advertising system, including infrastructure, models, and predictive components to improve ad relevance and ROI.

You will research AI technologies such as NLP, LLM, computer vision, andGenerative AI to interpret and generate ad creatives, while working with cross-functional teams on iterative improvements via A/B testing.