Join Microsoft Ads and build the next generation of AI infrastructure powering a multi-billion dollar online advertising business. Contribute to solving real-world customer challenges and delighting millions of Bing users through big data and machine learning. This role offers a dynamic and fast-paced environment where innovation is encouraged.

Our team engineers robust, massively scalable streaming systems and services crucial to Bing's significant monetization engine. We cover all facets of online advertising, including demand ingestion, management, and insights, as well as the preparation and low-latency serving of vast amounts of advertising data. Industry competition presents unique opportunities and technical challenges in Big Data, Distributed Systems, and Machine Learning/Deep Learning.

Key responsibilities include designing and implementing infrastructure features for ads metrics, alerting, diagnostics, and monitoring. You will optimize data processing pipelines and enhance architectures for peak performance and cost efficiency.

Further duties involve improving flight analysis infrastructure to boost CTS and introduce new business metrics. You'll conduct in-depth data analysis to inform technical designs and feature roadmaps. Collaboration with partner ads and Bing teams to enable various ad scenarios and leverage their advancements is also essential. Operational support, including bug fixes and live site issue resolution, is expected.

A Bachelor's Degree in Computer Science or a related technical field is required, coupled with at least 4 years of technical engineering experience, including coding in languages such as C, C++, C#, Java, JavaScript, or Python, or equivalent experience.

Preferred qualifications include a Bachelor's Degree in Computer Science or a related technical field with 8+ years of technical engineering experience in the aforementioned programming languages. Alternatively, a Master's Degree in Computer Science or a related technical field with 6+ years of technical engineering experience in these languages is desirable. Experience with large-scale big data systems like Cosmos, Hadoop, or Magnetar, building or operating streaming data pipelines (real-time/near-real-time), and proficiency with Apache Spark and Scala are highly valued.