NVIDIA · 2 days ago
Senior Deep Learning Performance Architect
Austin, TX
Full-time
Onsite
Senior Level
$184K/yr - $288K/yr
6+ years expNVIDIA is seeking outstanding Performance Architects to help analyze and develop the next generation of architectures that accelerate AI and high-performance computing applications. The role involves developing innovative hardware architectures, conducting studies on hardware configurations, and working closely with architecture and product teams to guide the hardware/software roadmap.
AI InfrastructureArtificial Intelligence (AI)Consumer ElectronicsFoundational AIGPUHardwareSoftwareVirtual Reality
Responsibilities
Develop innovative HW architectures to extend the state of the art in parallel computing performance, energy efficiency and programmability
Build the mathematical frameworks required to reason about system availability and workload goodput at massive scales
Reason about overall Deep Learning workload performance under various scheduling, parallelization, and resiliency strategies
Conduct "what-if" studies on hardware configurations, infrastructure knobs, and workload strategies to identify optimal system-level trade-offs
Work closely with wider architecture and product teams to guide the hardware/software roadmap using data-driven performance and reliability projections
Build and refine high-level simulators in python to model the interaction between knobs that impact performance and resiliency
Qualification
Required
MS or PhD in a Computer Science, Computer Engineering, Electrical Engineering or equivalent experience
6+ years of relevant industry or research work experience
Strong background in analytical and probabilistic modeling
2+ years of experience in parallel computing architectures, distributed systems, or interconnect fabrics
A strong understanding of distributed deep learning workloads scheduling in large scale systems
Proficiency in Python for building performance and reliability models
Preferred
Direct experience managing or troubleshooting large-scale jobs—you understand how jobs actually fail and recover in production
Experience working with large-scale operational datasets (e.g., scheduler or hardware telemetry)
Knowledge of how orchestrators (e.g., Slurm, Kubernetes, PyTorch) manage workload recovery and job scheduling under failures
Ability to simplify and communicate rich technical concepts with a non-technical audience
Benefits
Equity
Benefits
Company
NVIDIA
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI.
10001+ employees
H1B Sponsorship
NVIDIA has a track record of offering H1B sponsorships. Please note that this does not
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Funding
Current Stage
Public CompanyTotal Funding
$4.09BKey Investors
ARPA-EARK Investment ManagementSoftBank Vision Fund
2023-05-09Grant· $5M
2022-08-09Post Ipo Equity· $65M
2021-02-18Post Ipo Equity
Leadership Team
Jensen Huang
Founder and CEO
Michael Kagan
Chief Technology Officer
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