Solutions Architect, Data Processing - New College Grad 2026

Nvidia

Remote

Quick summary

Work type
Remote
Location
Santa Clara, CA
Salary
$124,000–$195,500 / yr
Posted
43 days ago

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $192k
This role $160k
$111k most similar roles pay here $249k

This role pays less than 65% of similar roles. Most pay $148,250–$235,750 — the shaded band above. At the midpoint, this role pays about $160k versus about $192k 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 563 open roles on FindRole.

Listed pay typically runs $168,000–$264,500 across 556 roles with salary data.

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At a glance

TL;DR · Solutions Architect, Data Processing - New College Grad 2026

As a senior researcher joining NVIDIA’s Solution Architecture Team, you will delve into cutting-edge research and development to accelerate databases and data analytics applications using GPU technology. Your daily tasks include collaborating with industry and academic experts to optimize complex workloads for current GPU architectures, pushing the boundaries of data processing performance. You will need a strong background in computer science or related fields, proficiency in C/C++, and expertise in low-level parallel programming techniques such as CUDA. Additionally, you should have deep knowledge of CPU/GPU architecture fundamentals, particularly memory subsystems, and hands-on experience with high-performance databases, ETL processes, and data analytics. This role is at the forefront of GPU-accelerated computing, addressing critical bottlenecks in data preprocessing and engineering for machine learning and deep learning applications by optimizing memory management, compression, and parallel algorithms across multi-GPU systems and distributed nodes.

What you'll do

  • Research and develop techniques to accelerate databases using GPUs.
  • Analyze and optimize complex data-intensive workloads for current GPU architectures.
  • Collaborate with technical experts to ensure optimal performance of data applications.
  • Influence partners to innovate in data processing using NVIDIA’s full product line.
  • Optimize database operators or query planners for parallel or distributed frameworks.
  • Profile and optimize CUDA kernels for enhanced performance.
  • Develop expertise in memory management, compression, and storage systems.

What we're looking for

  • Masters or PhD in Computer Science, Engineering, or related field.
  • Proficient in C/C++ with expertise in algorithms and software design.
  • Experience with low-level parallel programming (CUDA preferred).
  • Deep understanding of CPU/GPU architecture, focusing on memory subsystems.
  • Expertise in high performance databases, ETL processes, and data analytics.
  • Background in optimizing database operators or query planners for parallel systems.
  • Proficiency in profiling and optimizing CUDA kernels.

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