Overview

Microsoft Advertising is seeking a highly experienced Software Engineer to join our Ads Engineering Platform team to design and build next-generation Ads products that drive revenue growth and create innovative advertising experiences for users and advertisers.

You will play a key role in evolving the core capabilities of our ad-serving infrastructure—the engine that powers advertising across Bing Search, MSN, Microsoft Start, and shopping experiences in Microsoft Edge.

Our serving stack operates at massive global scale, delivering millions of ad requests per second through a geo-distributed, low-latency system that integrates real-time bidding, intelligent ranking, and ML-driven decisioning pipelines. We leverage a mix of CPU and GPU-based inference to balance latency, throughput, and cost efficiency.

This role combines product innovation, distributed systems architecture, and performance engineering. You will help shape both new monetization capabilities and the next generation of model serving infrastructure that powers them.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

• Responsibilities- Design and build new Ads products and monetization capabilities that unlock incremental revenue and enhance advertiser and end-user experiences.
• Lead the development of large-scale, distributed online serving systems to process millions of ad requests per second with ultra-low latency and high reliability. Architect and evolve ML-powered ranking and inference platforms across CPU and accelerator-based environments.
• Optimize end-to-end performance across model serving, batching, caching, scheduling, and traffic management to improve latency and cost efficiency. Drive system-level performance tuning using profiling, instrumentation, and production telemetry—improving tail latency and resource utilization.
• Own live-site reliability as a DRI for critical services in globally distributed systems.
• Collaborate with product and data science teams to translate business goals into scalable technical architecture. Mentor engineers and influence architectural direction across the Ads platform organization.

Qualifications:

Required Qualifications:

• Bachelor's Degree in Computer Science or related technical field AND 10+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or PythonOR equivalent experience.

Preferred Qualifications:

• Master's Degree in Computer Science or related technical field AND 12+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or PythonOR Bachelor's Degree in Computer Science or related technical field AND 15+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
• OR equivalent experience.
• Experience with Ads platforms, real-time bidding systems, or large-scale monetization systems.
• Familiarity with GPU performance optimization concepts such as batching strategies, memory movement, model quantization, and efficient resource scheduling.
• Experience with experimentation platforms (A/B testing), traffic ramping, and live-site incident management.
• Background in geo-distributed, high-availability production systems operating at Internet scale.
• Proifcient experience designing and operating real-time online serving or ranking systems.
• Proficient understanding of distributed systems fundamentals: concurrency, multi-threading, memory management, networking, and fault tolerance.
• Experience building or operating production ML inference systems, including performance optimization across CPU and/or GPU-based environments.
• Demonstrated ability to diagnose performance bottlenecks and improve latency, throughput, and cost efficiency in high-traffic systems.
• Proficient system design skills with the ability to translate product requirements into scalable technical solutions.

#MicrosoftAI

Software Engineering IC6 - The typical base pay range for this role across the U.S. is USD $163,000 - $296,400 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $220,800 - $331,200 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.