Software Engineer, CUDA Deep Learning Systems
Nvidia
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How this pay compares to similar roles
This role pays more than 78% of similar roles. Most pay $178,150–$235,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $207k for comparable roles.
Based on 240 similar postings.
Employer
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has 896 open roles on FindRole.
Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.
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At a glance
As a Senior Software Engineer, CUDA Deep Learning Systems, you will join a research-oriented team focused on the intersection of deep learning architectures and low-level hardware optimization. You will research and prototype system optimizations for advanced models, architect distributed computing systems that scale from single nodes to supercomputer clusters, and develop custom high-performance CUDA kernels tailored to emerging neural network workloads. Your daily work involves analyzing hardware-software interactions to resolve bottlenecks in training and inference pipelines while collaborating with architects and compiler experts to improve memory bandwidth and communication efficiency. You will utilize C++, Python, and CUDA programming to optimize generative AI models, including large language models and diffusion models. The role addresses the technical challenge of maximizing accelerator compute utilization for complex deep learning frameworks like PyTorch and JAX through advanced kernel optimization and distributed machine learning techniques.
What does a Software Engineer earn in California?
Median $214000 from 775 postings across 63 companies.
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