Job Description

About Us

Mintegral is a leading programmatic and interactive mobile advertising platform, starting from the APAC region and radiating out globally. Powered by advanced AI technology, we provide global advertisers and developers with innovative, comprehensive experiences. With our efficient mobile marketing and monetization solutions, we help our clients exceed their marketing goals.

As a self-developed programmatic platform, since Launched in 2015, Mintegral has quickly grown to become one of the largest mobile advertising platform in Asia. We offer a full stack of programmatic products and services including our Self-service Platform, DSP, SSP, Ad Exchange and DMP. We have also created the Mindworks Creative Studio, which offers publishers and brands cutting-edge creative solutions, from traditional creative right through to the latest interactive ad formats. For more information, please visit our website:

About the Role

We are looking for a highly motivated Machine Learning Engineer to help advance the intelligence of our advertising platform. You will work across the full lifecycle of ML development—from framing ambiguous problems to deploying large-scale production models that directly impact advertiser ROI and user experience.

Responsibilities

1. Own the end-to-end algorithm development lifecycle , including problem formulation, solution design, experimental validation, and online deployment.
2. Leverage data analysis and algorithmic innovation to optimize model inference performance, enhance monitoring systems, and continuously improve both monetization efficiency and user experience within the advertising platform.
3. Identify potential issues and optimization opportunities across the ad delivery system. Actively participate in technical discussions, stay proactive in learning, and apply new technologies to solve real-world problems.
4. Track cutting-edge research in machine learning and incorporate advanced techniques into practical adtech applications.

Qualifications

1. Bachelor’s or Master’s degree in Computer Science, Software Engineering, AI, Mathematics, Physics, or a closely related technical field; strong academic background preferred.
2. Excellent problem-solving skills, with the ability to abstract complex problems, build models, and analyze large datasets .
3. Strong engineering fundamentals and production-quality coding skills (Python, C++, or related languages).
4. Self-driven, resilient, and able to navigate challenging problems with a proactive mindset.
5. Hands-on experience with optimizing ad systems end-to-end , and understanding system behavior through data loops and feedback cycles.
6. Practical experience with feature engineering, model architecture design, and sample distribution analysis ; background in generative recommendation or LLM-based approaches is a plus.
7. Experience in RTB and ads strategies , such as cold-start optimization, budget pacing, calibration, or bidding strategies, is strongly preferred.

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