Deep Learning Performance Architect
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Recruiter screen, a technical screen mixing resume deep-dive with live coding, a hiring-manager conversation, then a panel of three to five 45–60 minute rounds: coding, systems design under hardware constraints, a domain deep-dive, and behavioral. Highly team-specific — you interview directly with the team — with C++ depth expected almost universally and decisions sometimes taking five-plus weeks after the panel.
Read the full NVIDIA interview process →Description
NVIDIA is developing GPU and system architectures that accelerate deep learning and high-performance computing applications. We are looking for an expert deep learning performance architect to join our deep learning modelling, performance projections, analysis and optimization effort. In this position, you will have the chance to analyze deep learning performance on different hardware and software architecture and make a significant impact in a dynamic technology focused company
What you’ll be doing:
Analyze performance of various deep learning workloads on different architectures
Identify architecture and software performance bottlenecks
Explore new features and system configurations to achieve better performance and energy efficiency
What we need to see:
BSc. MS or PhD in relevant discipline (CS, EE, Math, etc.,)
3+ years of working experience in relevant directions (e.g., hardware system, datacenter hardware, LLM workloads on data center) will be a plus
Be familiar with GPU or accelerator-based deep learning platform and software stack
A strong background in computer architecture
Experience on system architecture design and performance optimization
Familiar with machine learning and deep learning frameworks