Senior Data Architect responsible for designing data architectures focused on digital transformation. Join Klee Group in enhancing organizational performance through data strategy and innovative solutions.
About the role
- Performance Architect at NVIDIA developing innovative hardware architectures for AI and high-performance computing. Collaborating on performance modeling and system-level optimizations across large-scale deep learning workloads.
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.
Requirements
- 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.
Benefits
- equity
- benefits
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