Senior AI Software Architect
Technology, Data & Digital · Software & Web Development · Software Engineering · Machine Learning · Embedded Systems
In short
Microsoft is seeking a Senior AI Software Architect to lead hardware and software innovation for their cloud infrastructure. This role involves driving software architecture, performance optimization, and hardware-software co-design for next-generation AI systems.
Responsibilities
- Lead end-to-end software architecture and performance optimization for AI accelerator platforms.
- Prototype and validate software capabilities across kernels, compiler and runtime layers, distributed training and inference frameworks, and serving infrastructure.
- Analyze workload behavior at scale to identify performance bottlenecks, numerical correctness issues, and system-level efficiency opportunities.
- Use workload insights to guide hardware-software co-design decisions across architecture, silicon, systems software, networking, and product teams.
- Define requirements, evaluate tradeoffs, and deliver practical solutions for production-scale AI systems.
Requirements
- 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++, C#, Java, JavaScript, or Python OR equivalent experience.
- Ability to meet Microsoft, customer and/or government security screening requirements.
- Microsoft Cloud Background Check required upon hire/transfer and every two years thereafter.
Desired Qualifications
- PhD in Computer Science, Computer Architecture, Electrical Engineering, Machine Learning, High-Performance Computing, or a related field OR Master's Degree in Computer Science, Electrical Engineering, Computer Engineering, or related field AND 3+ years technical engineering experience OR Bachelor's Degree in Computer Science, Electrical Engineering, Computer Engineering, or related field AND 5+ years technical engineering experience OR equivalent experience.
- Experience designing, building, or optimizing systems software for AI, machine learning, high-performance computing, or distributed systems.
- Experience analyzing large-scale AI training runs, including loss curves, convergence behavior, gradient flow, activation statistics, and numerical stability.
- Experience debugging training correctness issues such as gradient divergence, NaNs/Infs, optimizer behavior, mixed-precision instability, distributed synchronization bugs, or hardware/software numerical differences.
Benefits
- Eligible for benefits and other compensation.
- Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay
#AI#Software Architecture#Hardware Engineering#Cloud#Machine Learning#Systems Software#Distributed Systems