5 hours ago
Shanghai, ChinaStaff+
Responsibilities
- Create and improve C++ and CUDA libraries for high-performance GPU data processing.
- Accelerate data loading, parsing, joins, aggregations, I/O, data movement, memory management, and concurrency operations.
- Build performant solutions for warehouse and Lakehouse workloads across compute, networking, and distributed storage.
- Drive software initiatives from architecture through delivery with a globally distributed technical team.
- Support partner integrations, proofs of concept, performance tuning, and production issue resolution with the Sales/DevRel team and partners in China.
- Apply data analytics and ETL expertise to optimize GPU-accelerated data processing pipelines.
Requirements
- Bachelor’s degree in Computer Science, Computer Engineering, Electrical Engineering, or a related technical field, or equivalent practical experience.
- 15+ years of relevant software engineering experience involving systems software, distributed data platforms, storage, databases, or accelerated computing.
- Proficiency in C++ and CUDA programming.
- Strong knowledge of data processing, data analytics, and storage environments.
- Deep expertise in distributed storage, database/query engine internals, high-performance I/O, accelerated computing, or large-scale data platforms.
- Experience with distributed or object storage, table formats such as Iceberg and Parquet, Lakehouse architectures, and analytical engines.
- Familiarity with or contributions to SiriusDB, GPU-accelerated query engines, or related projects.
- Preferred experience includes RAPIDS cuDF, S3, Parquet, Iceberg, cross-stack performance optimization, complex distributed-system production support, and defining technical direction while implementing critical components.
Benefits
- NVIDIA offers highly competitive salaries and a comprehensive benefits package for employees and their families.
About Nvidia
Nvidia designs and sells GPUs and accelerated computing platforms for data centers, AI/ML, graphics, gaming, and automotive, monetizing through hardware, software platforms (CUDA, AI frameworks), and systems like DGX and networking. Customers include cloud providers, enterprises, researchers, and OEMs. Founded in 1993 and headquartered in Santa Clara, it is a public company traded on NASDAQ under NVDA.