Python Software Engineer - GPU Accelerated LLM Data Applications

November 7

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NVIDIA

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

10,000+

Description

• Develop and optimize Python-based data processing frameworks for large datasets on GPU • Contribute to the design and implementation of RAPIDS and other GPU-accelerated libraries • Lead development and iterative optimization of components for RAG pipelines • Collaborate with teams of LLM & ML researchers on GPU-accelerated data preparation pipelines • Implement benchmarking, profiling, and optimization of algorithms in Python for LLM applications • Build & evaluate POCs, and develop roadmaps for production level tools

Requirements

• Advanced degree in Computer Science, Computer Engineering, or a related field (or equivalent experience) • 5+ years of Python library development experience, including CI systems (GitHub Actions), integration testing, benchmarking, & profiling • Proficiency with LLMs and RAG pipelines: prompt engineering, LangChain, llama-index • Deep understanding of the PyData & ML/DL ecosystems, including RAPIDS, Pandas, numpy, scikit-learn, XGBoost, Numba, PyTorch • Familiarity with distributed programming frameworks like Dask, Apache Spark, or Ray • Visible contributions to open-source projects on GitHub • Active engagement (published papers, conference talks, blogs) in the data science community • Experience with production-level data pipelines, especially SQL-based • Experience with software packaging technologies: pip, conda, Docker images • Familiarity with Docker-Compose, Kubernetes, and Cloud deployment frameworks • Knowledge of parallel programming approaches, especially in CUDA C++

Benefits

• Competitive salary • Equity • Unique legacy of innovation • Diverse work environment