1 day ago
Shanghai, ChinaStaff+
Responsibilities
- Create and improve C++ and CUDA libraries for high-performance data processing and end-to-end storage-to-GPU compute paths.
- Accelerate data loading, parsing, joins, aggregations, I/O, data movement, memory management, and concurrency.
- Implement 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.
- Collaborate with Sales and DevRel on partner integrations, proofs of concept, performance tuning, and production issue resolution with 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, including substantial work in 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 optimizing I/O and data-movement paths across distributed or object storage, table formats, Lakehouse architectures, and analytical engines.
- Familiarity with or contributions to SiriusDB, GPU-accelerated query engines, or related projects.
- Familiarity with RAPIDS cuDF, S3, Parquet, and Iceberg is preferred.
- Experience with cross-stack performance optimization and diagnosing complex distributed-system production issues is preferred.
- Ability to define technical direction, implement critical components, and drive cross-team delivery is preferred.
Benefits
- Competitive salaries and a comprehensive benefits package are offered.
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.