Senior Developer Technology Engineer, High-Performance Databases

at Nvidia

USD 152,000-287,500 per year

SENIOR

✅ Hybrid

Tech Stack
Tag name is followed by "@" symbol and proficiency level value. About proficiency levels:

1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;

3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;

7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;

10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.

AI Algorithms @ 7 CUDA @ 4 Communication @ 6 Data Engineering @ 6 Deep Learning @ 6 ETL @ 6 GPU @ 6 MPI @ 4 Machine Learning @ 6 Networking @ 6 Parallel Programming @ 4 Prioritization @ 6 Spark @ 4

Details

NVIDIA is seeking a Senior Developer Technology Engineer for high-performance databases. The Developer Technology Team works on leading-edge technologies with visibility and impact on NVIDIA's products and platforms.

Responsibilities

Research and develop techniques to GPU-accelerate high-performance database and ETL applications.
Work directly with technical experts from industry and academia to perform in-depth analysis and optimization of complex, data-intensive workloads for current GPU architectures.
Influence the design of next-generation hardware architectures, software, and programming models in collaboration with NVIDIA's research, hardware, system software, libraries, and tools teams.
Research memory management, compression, parallel algorithms, and multi-GPU and multi-node scaling techniques for data analytics workloads.

Requirements

Master's degree or PhD in Computer Science, Computer Engineering, or a related computationally focused science discipline, or equivalent experience.
At least 5 years of relevant work or research experience.
Programming fluency in C/C++ with a deep understanding of algorithms and software design.
Hands-on experience with low-level parallel programming, such as CUDA, OpenACC, OpenMP, MPI, pthreads, or TBB.
In-depth expertise in CPU/GPU architecture fundamentals, especially memory subsystems.
Domain expertise in high-performance databases, ETL, and data analytics.
Good communication and organization skills, a logical approach to problem solving, and prioritization skills.

Preferred Qualifications

Experience optimizing the performance of distributed database systems and frameworks, such as production databases or Spark.
Background in compression, storage systems, networking, and distributed computer architectures.

Data analytics is a rapidly growing field in GPU-accelerated computing. Data preprocessing and data engineering are traditionally CPU-based and are becoming bottlenecks for machine learning and deep learning applications. Complex data analytics pipelines can benefit from optimizations in memory management, compression, parallel algorithms such as sort, search, join, aggregation, and groupby, as well as scaling to multiple GPUs and many nodes.

Relevant NVIDIA open-source projects include nvcomp, Distributed Join, and cuCollections.

Compensation and Benefits

The base salary is determined by location, experience, and the pay of employees in similar positions. The base salary range is USD 152,000–241,500 for Level 3 and USD 184,000–287,500 for Level 4. The position is also eligible for equity and benefits.

Applications will be accepted at least until March 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is an equal opportunity employer committed to fostering a diverse work environment.