NVIDIA is hiring a Python Software Engineer, GPU - Accelerated LLM Data Applications

NVIDIA is looking for a Python Software Engineer, GPU - Accelerated LLM Data Applications to join our team. You will develop and optimize Python-based data processing frameworks for GPU-accelerated LLM data applications, focusing on accelerating preprocessing pipelines for multi-modal dataset curation, deduplication, filtering, and classification for foundation model LLMs and RAG pipelines.

What You'll Do

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

What We're Looking For

• 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, LlamaIndex.
• 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.

Nice to Have

• 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++.

Technical Stack

• Python, RAPIDS, Pandas, numpy, scikit-learn, XGBoost, Numba, PyTorch
• Dask, Apache Spark, Ray
• LangChain, LlamaIndex
• CUDA C++, GitHub Actions, Docker, Kubernetes

Benefits & Compensation

• Salary: $148,000 USD - $235,750 USD + equity.
• Competitive salaries.
• Generous benefits package.
• Eligible for equity.

NVIDIA is widely considered one of the technology industry's most desirable employers. We are committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.