Software Engineer 2--Ads

MAI Ads team in Microsoft ARPD is responsible for providing the advertising industry with the state-of-the-art online advertising platform and service. Our team is at the core of this effort, working on the following research & development: Selection(recall), Relevance, User Response Prediction (Click Prediction and Conversion prediction), Autobidding, Large Language Model and Large Scale Machine Learning & Serving System. The team is a world-class R&D team of passionate and talented scientists and engineers who aspire to solve challenging problems and turn innovative ideas into high-quality products and services that can help hundreds of millions of users and advertisers, and directly impact our business.

• Bachelor, Master, PhD degree in CS/EE or related areas is required.
• 2+ years of industry experiences in software engineering.
• Solid experience of shipping high performance C++, python, C#, or equivalent language code software.
• Experience with machine learning and TensorFlow/PyTorch distributed training is preferred.
• Domain knowledge of ads, search or content services is a plus.
• Quick learning and solid problem solving and debugging skills.
• Good communication skill.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

• Design and implement distributed training system for machine learning models.
• Analyze performance and identify opportunities based on offline and online testing, develop, and deliver robust and scalable solutions, make direct impact to both user and advertisers experience.
• Collaborate with cross-functional teams to deliver high-quality solutions.