Python Software Engineer - GPU Accelerated LLM Data Applications

December 1

Apply Now

Receive Emails with Similar Jobs

NVIDIA

WebsiteLinkedInAll Job Openings

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

10,000+ employees

Founded 1993

🤖 Artificial Intelligence

🎮 Gaming

Description

• Develop and optimize Python-based data processing frameworks, ensuring efficient handling of large datasets on GPU-accelerated environments, vital for LLM training. • Contribute to the design and implementation of RAPIDS and other GPU-accelerated libraries, focusing on seamless integration and performance enhancement in the context of LLM training data preparation and RAG pipelines. • Lead development and iterative optimization of components for RAG pipelines, ensuring they demonstrate GPU acceleration & the best performing models for improved TCO. • Collaborate with teams of LLM & ML researchers in the development of full-stack, GPU-accelerated data preparation pipelines for multimodal models • Implement benchmarking, profiling, and optimization of innovative algorithms in Python in various system architectures, specifically targeting LLM applications. • Work closely with diverse teams to understand requirements, build & evaluate POCs, and develop roadmaps for production level tools and library features within the growing LLM ecosystem.

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

Benefits

• Equity • Benefits