Note: The job is a remote job and is open to candidates in USA. Microsoft is a leading technology company that develops AI software enabling the operation of AI models across various platforms. The Senior and/or Principal Software Engineer will design and implement systems stacks and tools, ensuring quality and integration with Azure, while collaborating with hardware teams and ML researchers.
Responsibilities
- Apply strong engineering principles for defining robust and maintainable architectures and designs
- Collaborate broadly across multiple disciplines from hardware designers to ML developers
- Help establish and drive the adoption of good coding standards and patterns
- Perform software development in C/C++, C#, Python, and other languages
- Identify requirements, scope solutions, estimate work, schedule deliverables
Skills
- Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C++, C, or Python OR equivalent experience
- Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
- Master's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C++, C, or Python
- OR Bachelor'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, or Python
- OR equivalent experience
- 3+ years of experience in systems programming (C, C++, Rust, C#, or similar), with a focus on low-level or performance-critical software
- Solid understanding of memory models, concurrency, and interprocess communication
- Experience working on infrastructure involving hardware interfaces or device communication (e.g., PCIe, DMA, RDMA, or similar)
- Familiarity with Graphics Processing Unit (GPU), Tensor Processing Unit (TPU), or other accelerator architectures and their runtime systems
- Experience implementing communication protocols or working with driver/kernel interfaces
- Exposure to observability or profiling tools (e.g., eBPF, trace buffers, performance counters, telemetry hooks)
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