Senior Software Engineer

Why work at Bing Fundamentals?

The Heterogenous Computing Architecture team within Microsoft’s Bing Platform Engineering team is seeking a highly motivated, independent Senior Software Engineer to join us in blazing the trail by developing world-leading AI infrastructure at datacenter scale. By leveraging the massive parallelism delivered by current and future computing hardware (e.g., GPUs and Brainwave FPGAs), the team accelerates many types of Deep Neural Networks (DNN) workloads, including large-scale inference and training. We are applying accelerated computing to challenging applications important to Microsoft and our customers, including Bing search. Our work includes developing, optimizing, deploying, and maintaining our ML accelerator software, infrastructure and tools. Working with Microsoft model developers and data scientists to deploy their models gives us the unusual opportunity of working across the whole DNN stack, from cutting-edge DNN models, techniques, and frameworks to various accelerator architectures. This cutting-edge development takes place in the context of a live, global-scale distributed system that touches millions of users daily.  

Required/Minimum Qualifications:

• Bachelor's Degree in Computer Science, or related technical disciplines AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, or Python
  • OR equivalent experience.
• Previous software development experience in all stages of a release cycle (design, implementation, and test) with ability to cover multiple job roles.
• Experience in compiler and/or automation tools and flows.
• research experience.

Preferred Qualifications:

- Familiarity with neural networks, ML frameworks (e.g., PyTorch and Tensorflow), and inference/training optimization techniques.

- Software development experience, particularly in high-performance, distributed and/or fault-tolerant systems.

- Proven experience in collaborative team environments and leading project initiatives.

- Proficiency in GPU programming (e.g., CUDA) and familiarity with CUDA libraries, OR in FPGA hardware and application development.

- Experience with container and orchestration technologies (e.g., Kubernetes, Docker) is a plus.

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.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. 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.

• Understand different DNN workloads (e.g., Transformers and LLMs) and map them efficiently to the underlying system and hardware architecture.  

• Apply state-of-the-art AI and machine learning techniques to build and optimize the system to continuously achieve improved performance and user experience. 

• Develop ML system infrastructure in C/C++/C# and Python. 
• Build end-to-end optimized ML inference solutions, working across ML frameworks, runtimes, and distributed hardware devices. 
• Design and build model deployment processes leveraging automation and scripts. 
• Participate in/lead designs, and write production-level, high-quality code. 
• Deploy and maintain software to meet significant reliability, security and service level requirements.
• Work in a team of software and hardware engineers to deploy working systems to a very large user base.