Role at a glance
- Job function
-
Software Engineering & IT Software Engineering
- Salary
- Not Disclosed
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 15+ years of experience in GPU system software, GPU firmware, or accelerator platform engineering.
- Education
- BS or MS in Computer Science, Electrical Engineering, or related field (or equivalent experience)
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Qualifications
Required: Deep understanding of GPU architecture and compute performance, multi-GPU fabric architectures, GPU firmware and driver-stack interactions, firmware update lifecycle management at scale, error handling and recovery, and GPU health monitoring and telemetry. Customer obsession and demonstrated success influencing engineering teams to improve quality and fleet manageability are also required.
Required
- GPU architecture internals, including streaming multiprocessors, GEMM execution, compute kernels, memory hierarchy, and firmware/driver...
- Multi-GPU fabric architectures such as NVLink and firmware coordination across rack-scale systems
- GPU firmware architecture, including VBIOS, GPU microcontroller firmware, InfoROM, and interaction with the GPU driver stack
- Firmware update lifecycle management at scale, including multi-device sequencing, A/B updates, rollback, staged rollout, and emergency...
- GPU error handling and recovery flows through the driver stack to application-visible failures
- GPU health monitoring and telemetry, including Xid errors, thermal and power events, and ECC counters
- Customer obsession and proven success influencing engineering teams to improve quality and fleet manageability
Preferred
- Direct experience with NVIDIA GPU VBIOS, GPU microcontroller firmware, or GPU driver internals
- GPU fleet management at 10K+ GPU scale, including firmware rollout, health-based remediation, and fleet-wide configuration management
- Experience with GPU error taxonomy and runbooks for GPU firmware behavior
- Understanding of GPU security, including secure boot chain, code signing, attestation, debug authentication, and firmware-level...
- Familiarity with GPU power management architecture and its impact on workload performance at fleet scale
About the role
Original posting provided by NVIDIA
We're looking for a Principal Software Engineer to join our CSP Engagements team as the technical focal point for GPU firmware and GPU system software, working directly with engineering teams of key CSP / hyperscale customers to ensure they can reliably manage, update, and operate NVIDIA GPU firmware at fleet scale. You will drive work streams with engineering teams of key CSPs/hyperscale customers to build shared understanding of GPU firmware and system software integration, incorporate their feedback into NVIDIA's feature roadmap and delivery plan, and ensure customer-side automation and recovery procedures are ready before each firmware release. Your cross-CSP visibility enables you to identify patterns in GPU firmware operational challenges that drive systemic improvements no single customer engagement could surface alone.
What you'll be doing:
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
What we need to see:
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
Ways to stand out from the crowd:
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
NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative, hardworking and self-motivated, we want to hear from you!
Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 272,000 USD - 431,250 USD.You will also be eligible for equity and benefits.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.About the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.