Senior Developer Technology Engineer, High-Performance Databases

Nvidia

Confirmed live 2 days ago High trust

Hybrid

Quick summary

Work type: Hybrid
Location: Santa Clara, CANew York, NY
Salary: $152,000–$241,500 / yr
Posted: 36 days ago
Freshness: Confirmed live 2 days ago
Nearby: 99+ roles within 25 mi

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Salary context

Competitive pay

How this pay compares to similar roles

Similar $187k

This role $197k

$139k most similar roles pay here $252k

This role pays more than 55% of similar roles. Most pay $149,962–$224,000 — the shaded band above. At the midpoint, this role pays about $197k versus about $187k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 896 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 876 roles with salary data.

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At a glance

TL;DR · Senior Developer Technology Engineer, High-Performance Databases

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Senior Developer Technology Engineer, High-Performance Databases joins the Developer Technology Team to research and develop techniques for GPU-accelerated high-performance database and ETL applications. This role involves performing in-depth analysis of complex data-intensive workloads, investigating hardware and system bottlenecks, and optimizing performance on current GPU architectures. The engineer will collaborate with internal teams and external experts from industry and academia to influence the design of next-generation hardware architectures, software, and programming models. Candidates must possess a master's or PhD in a related field and have at least five years of experience. Required skills include C/C++ proficiency, deep knowledge of algorithms, and expertise in low-level parallel programming using CUDA, OpenACC, OpenMP, MPI, pthreads, or TBB. The role focuses on the technical challenges of memory management, data analytics, and distributed database systems within a GPU-accelerated computing environment.

Skills

CUDA C++ C OpenACC OpenMP MPI pthreads TBB GPU Architecture High-Performance Databases ETL Spark Memory Management Parallel Programming Data Analytics Storage Systems Networking

What you'll do

Research and develop techniques to GPU-accelerate high-performance database and ETL applications.
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.
Collaborate with industry and academic experts to optimize performance of data-intensive systems.
Design parallel algorithms and implement optimizations in a GPU-accelerated computing environment.
Publish technical findings in developer blogs or at relevant conferences and workshops.
Provide application expertise to influence internal hardware and software product development.

What we're looking for

A Master's or PhD in Computer Science, Computer Engineering, or a related computationally focused science degree is required.
Candidates must have at least 5 years of relevant work or research experience.
Proficiency in C/C++ with a deep understanding of algorithms and software design is required.
Hands-on experience with low-level parallel programming such as CUDA, OpenACC, OpenMP, MPI, pthreads, or TBB is required.
In-depth expertise in CPU/GPU architecture fundamentals, specifically regarding the memory subsystem, is required.
Domain expertise in high-performance databases, ETL, and data analytics is required.
Strong communication, organization, and logical problem-solving skills are required.
Experience with distributed database systems, compression, storage systems, or networking is preferred.

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