Staff/Senior Machine Learning Scientist (Ad Cloud)

Appier is seeking a Senior Machine Learning Scientist to join our Advertising Cloud Optimization team, which leads the development of core machine learning algorithms driving campaign efficiency and advertiser ROI. Our programmatic advertising platform operates at a massive scale, handling over multi millions queries per second (QPS), all powered by our proprietary deep learning models for bidding, pricing, and personalized content delivery.

In this role, you’ll directly impact the efficiency and profitability of ads campaigns by improving models for bidding, pricing, and personalized content recommendation, while ensuring system robustness and scalability in a dynamic market environment.

Key responsibilities include designing, implementing, and productionizing state-of-the-art ML models to improve campaign outcomes. You will analyze large-scale user and auction data to discover predictive patterns and alpha signals that enhance bidding and personalization. Collaborating cross-functionally with engineering, product, and data teams, you will identify opportunities, define roadmaps, and deliver impactful solutions. Additionally, you will continuously improve system performance through offline experimentation and online testing, such as A/B tests and incremental learning.

The ideal candidate will have a Bachelor's degree in Computer Science, Mathematics, Electrical Engineering, or a related field, with a Master's or PhD preferred. A minimum of 4 years of industry experience in ad tech, focusing on performance optimization, is required. Proven experience in applied machine learning, especially in CTR prediction and recommendation systems, is essential. Proficiency in Python and experience with modern ML frameworks like PyTorch and TensorFlow are necessary. Strong ownership and collaboration skills, with the ability to lead end-to-end projects across product, data, and engineering, are also important. Experience working on high-throughput, low-latency real-time systems, such as RTB engines and stream inference, is a plus.