Solutions Architect, CSP GTM

Role overview A field-facing solutions architect role partnering with hyperscaler cloud providers on Physical AI, agentic AI, and machine learning workloads. The role serves as the first line of technical expertise between the company, its cloud partners, and end customers, helping shape how accelerated computing powers next-generation AI applications.

Responsibilities - Develop and demonstrate Physical AI solutions leveraging hyperscaler infrastructure and proprietary software and hardware - Work directly with key customers and cloud partners to understand their challenges and recommend suitable products - Perform in-depth analysis and optimization of GPU-accelerated training and inference pipelines - Partner with engineering, product, and sales teams to plan solutions and address developer challenges - Enable product feature growth through customer feedback and proof-of-concept evaluations - Build deep industry expertise integrating accelerated computing into enterprise architectures

Requirements - MS, PhD, or equivalent experience in Computer Science, Data Science, Electrical/Computer Engineering, Physics, Mathematics, or related engineering field - 5+ years in solutions architecture or engineering within AI-related domains - Strong written and verbal communication skills, with comfort presenting technical material in English - Hands-on expertise with Physical AI solutions deployed on hyperscaler infrastructure - Track record of academic or industry work in machine learning, deep learning, or data science - Self-starter mindset with a passion for continuous learning and cross-team collaboration

Nice to have - Background delivering Physical AI solutions and offerings through hyperscaler platforms - Experience running and optimizing large-scale distributed deep learning training and inference pipelines - Familiarity with transformer-based architectures at scale - DevOps expertise with Docker, Kubernetes, Singularity, and similar technologies