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Nvidia Engineering information
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$49.2K - $61.4K
1% of jobs
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1% of jobs
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5% of jobs
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7% of jobs
$120.7K is the 25th percentile. Wages below this are outliers.
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3% of jobs
The median wage is $172.2K / yr.
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52% of jobs
$49.2K
$155.3K
$184K
How much do nvidia engineering jobs pay per year?
What are the key skills and qualifications needed to thrive in the Nvidia Engineering position, and why are they important?
To thrive in Nvidia Engineering, candidates typically need strong proficiency in computer engineering, software development, and a solid understanding of hardware architecture, often backed by a relevant degree such as Electrical Engineering or Computer Science. Familiarity with tools like CUDA, C/C++, Python, and version control systems, as well as experience with GPU programming, are highly valued, and certifications such as Nvidia's Deep Learning Institute credentials can enhance a candidate's profile. Excellent problem-solving, team collaboration, and communication skills set top performers apart in this role. These skills and qualifications enable engineers to contribute effectively to complex, innovative projects that drive Nvidia's technological advancements.
What is an Nvidia Engineering job?
An Nvidia Engineering job involves designing, developing, and optimizing hardware or software solutions in areas such as graphics processing, AI, and high-performance computing. Engineers at Nvidia work on cutting-edge technologies, including GPUs, deep learning frameworks, and system architecture. Roles vary from hardware design and verification to software development and AI research, depending on expertise. Strong skills in programming, computer architecture, and problem-solving are typically required.
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What types of projects do Nvidia Engineers typically work on, and how is teamwork structured within the engineering department?
Nvidia Engineers commonly engage in projects related to GPU development, AI and deep learning solutions, software driver optimization, and next-generation hardware innovation. Project teams are often multidisciplinary, bringing together software, hardware, and systems engineers to collaborate closely on end-to-end product development. Engineers frequently work in agile, fast-paced environments, attend regular team stand-ups, and participate in cross-functional meetings. This collaborative structure fosters creativity, accelerates problem-solving, and ensures high-quality product delivery while offering team members exposure to diverse technologies and career growth opportunities.
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How much do NVIDIA application engineers make?
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Full-time
Posted 20 days ago
Nvidia rating
9.3
Based on 5 frontline employees who took The Breakroom Quiz
15th of 209 rated software companies
Job description
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 Nvidia
Sourced by ZipRecruiter
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.
Industry
Computer and electronic product manufacturing
Company size
10,000+ Employees
Headquarters location
Santa Clara, CA, US
Year founded
1993