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Senior AI Software Architect

United States, Washington, Redmond💼 Full-time🗓 2026-07-13 → 2026-07-18

Core

Lead end-to-end software architecture and performance optimization for AI accelerator platforms, guiding hardware-software co-design decisions.

Role type

Senior AI Software Architect

Builds

Production-scale AI systems, distributed training and inference frameworks, and serving infrastructure.

Domain

AI, Machine Learning, High-Performance Computing, Distributed Systems

Deliverable

production ML models | infrastructure

Required skills

C, C++, C#, Java, JavaScript, Python, system software design, performance optimization, workload analysis, numerical correctness debugging, distributed synchronization debugging, hardware-software co-design

Preferred skills

Experience with loss curves, convergence behavior, gradient flow, activation statistics, mixed-precision instability

Technologies

Kernels, compilers, runtime layers, distributed training frameworks, inference frameworks

Responsibilities

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; Define requirements, evaluate tradeoffs, and deliver practical solutions for production-scale AI systems

Seniority

Senior, hands-on IC

Rewrite
## About the role 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. - These requirements include, but are not limited to, the following specialized security screenings: - PhD in Computer Science, Computer Architecture, Electrical Engineering, Machine Learning, High-Performance Computing, or a related field - Master's Degree in Computer Science, Electrical Engineering, Computer Engineering, or related field AND 3+ years technical engineering experience - 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. ## Nice to have - None specified in the original text. ## What we offer - None specified in the original text. ## About us - None specified in the original text.
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