Senior Software Engineer

September 30

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Logo of NVIDIA

NVIDIA

GPU-accelerated computing • artificial intelligence • deep learning • virtual reality • gaming

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Description

• Develop and enhance functionalities within the GenAI-Perf, Triton Performance Analyzer and Triton Model Analyzer tools. • Collaborate with researchers and engineers to understand their performance analysis needs and translate them into actionable features. • Collaborate closely with cross-functional teams including software engineers, system architects, and product managers to drive performance improvements throughout the development lifecycle. • Responsible for setting up, executing, and analyzing the performance of LLM, Generative AI and deep learning models. • Develop and implement efficient algorithms for measuring deep learning throughput and latency, benchmarking large language models, and deploying models. • Integrate various tools to create a unified and user-friendly experience for deep learning performance analysis. • Automate testing processes to ensure the quality and stability of the tools. • Contribute to technical documentation and user guides. • Stay up-to-date on the latest advancements in deep learning performance analysis and LLM optimization techniques.

Requirements

• Bachelor's, Masters or PhD or equivalent experience • 4+ years in Computer Science, computer architecture, or related field • Knowledge of distributed systems programming. • Ability to work in a fast-paced, agile team environment • Excellent Python programming and software design skills, including debugging, performance analysis, and test design. • Experience with deep learning algorithms and frameworks. • Excellent troubleshooting abilities spanning multiple software (storage systems, kernels and containers). • Experience contributing to a large open source project - use of GitHub, bug tracking, branching and merging code, OSS licensing issues handling patches, etc. • Familiarity with cloud computing platforms (e.g., AWS, Azure, GCP) and Experience building and deploying cloud services using HTTP REST, gRPC, protobuf, JSON and related technologies. • Experience working with NVIDIA GPUs and deep learning inference frameworks is a plus.

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