Remote Position
[Remote] Principal Software Engineer- AI Frameworks
🌍 Remote · United States
💼 Full-time
Note: The job is a remote job and is open to candidates in USA. Microsoft develops software, performance systems, and engineering tools that enable state-of-the-art AI models to run reliably and efficiently at cloud scale. The Principal Software Engineer will set technical direction and lead hands-on, cross-stack initiatives across AI frameworks, performance engineering, benchmarking, and tooling to improve model velocity, platform efficiency, and production reliability.
Responsibilities
- Define technical vision, architecture, and multi-release strategy for critical AI framework, performance, benchmarking, or developer-productivity capabilities
- Lead ambiguous, cross-stack investigations and investments spanning models, frameworks, compilers, runtimes, systems, services, and silicon
- Establish common measurement, automation, observability, and engineering mechanisms that turn one-off analyses into scalable platform capabilities
- Drive measurable improvements in model onboarding velocity, runtime performance, reliability, hardware utilization, and Azure capacity efficiency
- Influence architecture and priorities across teams; align researchers, product groups, infrastructure owners, and hardware partners around clear decisions and execution plans
- Provide hands-on technical leadership through prototypes, critical-path implementation, design and code reviews, complex debugging, and operational readiness
- Raise the engineering bar by mentoring engineers, developing technical leaders, and advancing standards for quality, maintainability, and inclusive collaboration
- Embody Microsoft’s culture and values
Skills
- Bachelor's Degree in Computer Science or a related technical field and 6+ years of technical engineering experience coding in languages such as 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
- Deep expertise in GPU or equivalent accelerator programming, compilation, and low-level execution, including intermediate representations, lowering, code generation, instruction-level behavior, memory hierarchy, and synchronization
- Expertise in parallelism strategies used in LLM training and inference, including tensor, pipeline, data, and expert parallelism, with the ability to evaluate their suitability for different models and hardware configurations
- Expertise in distributed inference acceleration, including prefill/decode disaggregation, KV-cache transfer, collective communication, and compute/communication overlap
- Strong understanding of LLM serving architectures such as vLLM, SGLang, or equivalent systems, with a track record of translating architectural improvements into measurable production gains
- Demonstrated leadership of cross-team technical initiatives from strategy and design through implementation, deployment, and sustained production impact
- A track record of creating reusable platforms, influencing stakeholders, and mentoring engineers
- Ability to use AI-assisted development tools effectively and establish practices that improve engineering productivity without compromising correctness, performance, or maintainability
Benefits
- Certain roles may be eligible for benefits and other compensation.
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