Principal Software Engineer, GPU Firmware and GPU System Software — CSP Engagements

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. They are seeking a Principal Software Engineer to join their CSP Engagements team as the technical focal point for GPU firmware and GPU system software, working directly with engineering teams of key CSP customers to ensure reliable management and operation of NVIDIA GPU firmware at fleet scale.

Responsibilities:

• Drive GPU firmware & siftware work streams with CSP engineering teams — ensuring they understand GPU firmware architecture (VBIOS, InfoROM, microcontroller firmware), update sequencing, recovery procedures, and GPU power management
• Gather and synthesize CSP feedback on GPU firmware/software — covering manageability, observability, security requirements (e.g., multi-tenancy isolation, secure boot, attestation), and performance — and champion those priorities into NVIDIA's GPU firmware/software feature roadmap and delivery plan
• Drive GPU firmware update orchestration for large-scale deployments — multi-GPU update sequencing, rollback strategy, failure handling, and validation across hundreds of GPUs per rack
• Serve as the technical focal point between NVIDIA and CSP firmware/software engineering — ensuring GPU behaviors (error recovery flows, thermal protection, power state transitions) are well-documented and accessible for customer integration
• Identify cross-CSP GPU SW/FW issue patterns — common update failures, recovery gaps, and configuration problems — and drive documentation, tooling, and test strategy improvements

Requirements:

• 15+ years of experience in GPU system software, GPU firmware, or accelerator platform engineering. BS or MS in Computer Science, Electrical Engineering, or related field (or equivalent experience)
• Deep understanding of GPU architecture internals: streaming multiprocessors, GEMM execution, compute kernels, memory hierarchy, and how firmware/driver decisions impact GPU compute performance
• Understanding of multi-GPU fabric architectures (NVLink, or similar) and how firmware coordinates across multiple GPUs in a rack-scale system
• Understanding of GPU firmware architecture: VBIOS, GPU microcontroller firmware, InfoROM, and their interaction with the GPU driver stack
• Experience with firmware update lifecycle management at scale: multi-device update sequencing, A/B updates, rollback, staged rollout, emergency recovery
• Understanding of GPU error handling and recovery flows — how firmware-level errors propagate through the driver stack to application-visible failures
• Experience with GPU health monitoring and telemetry: Xid errors, thermal events, power events, ECC counters, and their significance for firmware/software teams
• Customer obsession — genuine passion for simplifying GPU firmware integration for fleet-scale customers. Proven success influencing engineering teams to improve quality and fleet manageability
• Direct experience with NVIDIA GPU VBIOS, GPU microcontroller firmware, or GPU driver internals
• Background in GPU fleet management at 10K+ GPU scale — firmware rollout, health-based remediation, fleet-wide configuration management
• Experience with GPU error taxonomy (Xid classification, NVLink error counters, ECC events) and building runbooks around GPU firmware behavior
• Understanding of GPU security: secure boot chain, code signing, attestation, debug authentication, multi-tenancy isolation at the firmware level
• Familiarity with GPU power management architecture and its impact on workload performance at fleet scale