Principal Software Engineer - Maia Model Enablement

About the job

Define and drive the technical strategy required to enable new AI models, model architectures, and hardware generations on Maia. Lead complex cross-stack investigations spanning models, serving systems, infrastructure, and hardware, driving resolution of systemic technical challenges. Drive platform-wide improvements in performance, scalability, and serving capabilities that benefit multiple models and future hardware generations. Create durable automation, validation, and engineering systems that improve the speed, reliability, and repeatability of model enablement across the organization. Align model, software, infrastructure, and hardware teams around shared technical direction, execution plans, and long-term platform investments. Performance, scalability, and reliability improvements benefit broad classes of workloads rather than individual deployments. 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. Understanding of modern AI model architectures, inference systems, performance optimization, and serving stacks. Experience diagnosing and resolving complex problems that span models, software, systems, infrastructure, and hardware. Experience enabling software on new hardware platforms, accelerators, or large-scale systems through activities such as bring-up, performance characterization, hardware-software debugging, or platform enablement. Experience leveraging modern engineering tools, including AI-assisted workflows, automation, and agents, to improve productivity and accelerate technical investigation. Demonstrated ability to identify high-impact technical investments, drive them from concept through production, and create durable capabilities that improve how engineering work is performed. Technical judgment and experience leading cross-team technical initiatives across complex and ambiguous problem spaces. Ability to balance immediate delivery needs with long-term platform strategy and architectural direction.