Senior Software Engineer at Microsoft

Redmond, Washington, United States -

Full Time

Start Date

Immediate

Expiry Date

05 Mar, 26

Salary

234700.0

Posted On

05 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

C++, GPU Inference, CUDA, TensorRT, Model Serving, Performance Engineering, Real-Time Data Streaming, Multi-Threading, Process Scheduling, NUMA-Aware Memory Allocation, Deep Learning, LLM Workloads, Fault-Tolerance Mechanisms, Telemetry, System Optimization, Cross-Functional Collaboration

Industry

Software Development

Description

Overview Microsoft Advertising is seeking a Senior Software Engineer to join our Ads Engineering Platform team and advance the core capabilities of our ad-serving infrastructure—the engine that powers advertising across Bing Search, MSN, Microsoft Start, and shopping experiences in the Edge browser. Our serving stack operates at massive global scale, delivering millions of ad requests per second through a geo-distributed, low-latency system that combines large-scale GPU/CPU inference, real-time bidding, and intelligent ranking pipelines. This role focuses on advancing the performance, efficiency, and scalability of the next generation of model serving and inference platforms for Ads.As a senior technical leader, you’ll design and optimize high-performance serving systems and GPU inference frameworks that drive measurable latency improvements and cost efficiency across Microsoft’s ad ecosystem. You’ll work across the stack—from CUDA kernel tuning and NUMA-aware threading to large-scale distributed orchestration and model deployment for deep learning and LLM workloads. This is a rare opportunity to shape the architecture of one of the world’s most advanced, mission-critical online serving platforms, collaborating with world-class engineers to deliver innovation at Internet scale. Responsibilities Design and lead the development of large-scale, distributed online serving systems—including GPU-accelerated and CPU-based ranking/inference pipelines—to process millions of ad requests per second with ultra-low latency, high throughput, and strong reliability. Architect and optimize end-to-end inference infrastructure, including model serving, batching/streaming, caching, scheduling, and resource orchestration across heterogeneous hardware (GPU, CPU, and memory tiers). Profile and optimize performance across the full stack—from CUDA kernels and GPU pipelines to CPU threads and OS-level scheduling—identifying bottlenecks, tuning latency tails, and improving cost efficiency through advanced profiling and instrumentation. Own live-site reliability as a DRI: design telemetry, alerting, and fault-tolerance mechanisms; drive rapid diagnosis and mitigation of performance regressions or outages in globally distributed systems. Collaborate and mentor across teams—driving architecture reviews, enforcing engineering excellence, promoting system-level optimization practices, and mentoring others in deep debugging, profiling, and performance engineering. Qualifications Required/minimum qualifications Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience developing high-performance, distributed systems in C++ OR equivalent experience. Additional or preferred qualifications Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience developing high-performance, distrbuted systems in C++ OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineeringexperience developing high-performance, distrbuted systems in C++ OR equivalent experience. Deep expertise in GPU inference frameworks such as NVIDIA Triton Inference Server, CUDA, and TensorRT, including hands-on experience implementing custom CUDA kernels, optimizing memory movement (H2D/D2H), overlapping compute and I/O, and maximizing GPU occupancy and kernel fusion for deep learning and LLM workloads. Strong understanding of model-serving trade-offs—batching vs. streaming, latency vs. throughput, quantization (FP16/BF16/INT8), dynamic batching, continuous model rollout, and adaptive inference scheduling across CPU/GPU tiers. Proven ability to profile and optimize GPU and system workloads—including tensor/memory alignment, compute–memory balancing, embedding table management, parameter servers, hierarchical caching, and vectorized inference for transformer/LLM architectures. Expertise in low-level system and OS internals, including multi-threading, process scheduling, NUMA-aware memory allocation, lock-free data structures, context switching, I/O stack tuning (NVMe, RDMA), kernel bypass (DPDK, io_uring), and CPU/GPU affinity optimization for large-scale serving pipelines. Hands-on experience with real-time data streaming systems (Kafka, Flink, Spark Streaming), feature-store integration, and multi-region deployment for low-latency, globally distributed services. Familiarity with LLM inference optimization—model sharding, tensor/kv-cache parallelism, paged attention, continuous batching, quantization (AWQ/FP8), and hybrid CPU–GPU orchestration. Demonstrated success operating large-scale systems with SLA-based capacity forecasting, autoscaling, and performance telemetry; proven leadership in cross-functional architecture initiatives and technical mentorship. Passion for performance engineering, observability, and deep systems debugging, with a strong drive to push the limits of serving infrastructure for the next generation of ads and AI models. Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 $158,400 - $258,000 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.

Responsibilities

Design and lead the development of large-scale, distributed online serving systems to process millions of ad requests per second. Collaborate and mentor across teams to drive architecture reviews and promote system-level optimization practices.