Principal Networking AI Systems Architect

Benefits

• ting from AI/ML.
• Drive the integration of AI capabilities into system architecture and engineering workflows.
• Identify system-level opportunities for failure management, automated troubleshooting, performance improvement, and resource optimization.
• Translate system behavior, dependencies, data, and operational constraints into formulated research problems.
• What we need to see: Ph.D in electrical engineering, machine-learning, computer-science or another relevant field. 10+ years of deep technical experience in high-performance network architecture, data center networking, or distributed systems design.
• Mastery of high-speed interconnect protocols including InfiniBand and/or advanced Ethernet architectures.
• Thorough experience driving high-impact projects centered on modern AI/ML such as LLMs/agents, deep-learning, black-box optimization or another relevant field.
• Deep knowledge of AI/ML and networking-hardware/system-architecture.
• Excellent ability to convey and communicate data-based insights to stakeholders and management.
• Experience demonstrating an excellent track of collaboration with hands-on teams.
• Ways to stand out from the crowd: Demonstrated track record of architecting and deploying multi-thousand-node GPU clusters for hyperscale cloud environments.
• Deep knowledge of NVIDIA networking technologies, including BlueField DPUs, Quantum InfiniBand switches, and Spectrum Ethernet platforms.
• Expertise in in-network computing, telemetry, adaptive routing, and telemetry-driven network optimization.
• High energy and a positive, proactive and curious approach.