DevRel Lead — GPU-Accelerated Analytics

NVIDIA Gruppe; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA is building GPU acceleration for analytical data processing ecosystems. This role focuses on query planning, vectorized processing, and integration across engines, libraries, and tools.

You will benchmark, advise, and shape roadmaps, collaborating with architects and partners to land acceleration across cloud, hybrid, and on-prem deployments. The position requires 6+ years in software/engineering with analytical data systems and strong C++, Python, or Rust skills.

Qualifications

• Bachelor's or Master's degree in CS/Engineering or related field.
• 6+ years in software engineering, developer relations, or related areas with analytical data systems.
• Experience with open source data projects and data platforms.
• Deep knowledge of query execution, vectorized and columnar processing, joins, and storage formats.
• Reading/contributing to large C++, Rust, or Python codebases.
• Strong communication and cross-functional collaboration skills.

Responsibilities

• Build and deepen technical expertise in analytical data processing and serve as a technical advocate.
• Demonstrate and integrate NVIDIA's data processing stack into real engines and OLAP databases.
• Support onboarding with reference implementations and hands-on engineering help.
• Track new engines and formats; share learnings to shape NVIDIA's roadmap.
• Collaborate with engine architects to resolve integration problems and set best practices.
• Define the integration surface and APIs to connect NVIDIA libraries with third-party engines.
• Own benchmark evidence for GPU-accelerated analytics and publish results with robust methodology.
• Shape the acceleration roadmap with projects and partners through architecture reviews.

Skills

Query planning & processing

Columnar processing

Vectorized processing

SQL engine internals

C++

Python

Rust

Parquet

Arrow

Effective communication

Education

Bachelor's or Master's degree

Tools

Parquet

Arrow

CUDA-X libraries

Job description

NVIDIA is building GPU acceleration for analytical data processing ecosystems. This role focuses on query planning, vectorized processing, and integration across engines, libraries, and tools.

You will benchmark, advise, and shape roadmaps, collaborating with architects and partners to land acceleration across cloud, hybrid, and on-prem deployments. The position requires 6+ years in software/engineering with analytical data systems and strong C++, Python, or Rust skills.