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NVIDIA

Developer Technology Engineer, High-Performance Databases – New College Grad 2026

NVIDIA · Santa Clara, California, US
full-timejunior (0-2 yrs)Posted 29d ago
Developer Technology EngineeringIC2ICOn-siteVisa Sponsored
StackCC++CUDAOpenACCOpenMPMPIpthreadsTBBGPU architectureCPU architectureparallel programmingdistributed computingApache Sparkvector databasesNVIDIA nvcompcompression algorithmsmemory managementquery planningdatabase operators

Summary

Entry-to-mid level DevTech Engineer role at NVIDIA focused on GPU-accelerating high-performance databases, ETL pipelines, and data analytics workloads. Involves deep algorithm research, CUDA kernel optimization, and hardware architecture influence for new grad Masters/PhD candidates.

About the role

Our work at NVIDIA is dedicated towards a computing model focused on visual and AI computing. For two decades, NVIDIA has pioneered visual computing, the art and science of computer graphics, with our invention of the GPU. The GPU has also shown to be spectacularly effective at solving some of the most complex problems in computer science. Today, NVIDIA’s GPU simulates human intelligence, running deep learning algorithms and acting as the brain of computers, robots and self-driving cars that can perceive and understand the world. We are looking to grow our company and teams with the smartest people in the world and there has never been a more exciting time to join our team! 

NVIDIA is currently seeking a Developer Technology Engineer for High-Performance Databases! Would you enjoy researching new algorithms and memory management techniques to accelerate databases on modern computer architectures? Do you like investigating hardware and system bottlenecks, and optimizing performance of data intensive applications? Are you excited about the opportunity to work on the top tier edge of technology with both visibility and impact to the success of a leader like NVIDIA? If so, the Developer Technology Team invites you to consider this opportunity.

What you will be doing:

  • In this role, you will research and develop techniques to GPU-accelerate high performance database, ETL and data analytics applications.

  • Work directly with other technical experts in their fields (industry and academia) to perform in-depth analysis and optimization of complex data intensive workloads to ensure the best possible performance of current GPU architectures.

  • Influence the design of next-generation hardware architectures, software, and programming models in collaboration with research, hardware, system software, libraries, and tools teams at NVIDIA

What we need to see:

  • Pursuing or recently completed Masters or PhD in Computer Science, Computer Engineering, or related computationally focused science degree or equivalent experience.

  • Programming fluency in C/C++ with a deep understanding of algorithms and software design.

  • Hands-on experience with low-level parallel programming, e.g. CUDA (preferred), OpenACC, OpenMP, MPI, pthreads, TBB, etc.

  • In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystem.

  • Domain expertise in high performance databases, ETL, data analytics and/or vector database.

  • Good communication and organization skills, with a logical approach to problem solving, and prioritization skills.

Ways to stand out from the crowd:

  • Experience optimizing/implementing database operators or query planner, especially for parallel or distributed frameworks (e.g. production database or Spark).

  • Experience optimizing vector database index build and/or search.

  • Experience profiling and optimizing CUDA kernels.

  • Background with compression, storage systems, networking, and distributed computer architectures.

Data Analytics is one of the rapidly growing fields in GPU accelerated computing. Data preprocessing and data engineering are traditionally CPU based and are becoming the bottleneck for Machine Learning (ML) and Deep Learning (DL) applications, as performance of the frameworks and core ML/DL libraries has been highly optimized leveraging GPUs. Many of today’s applications have complex data analytics pipelines that can benefit from optimizations in memory management, compression, parallel algorithms like sort, search, join, aggregation, groupby, scaling up to multi GPU systems, and scaling out to many nodes. Take a look at some of the open-source projects that our Devtech team have worked on: NVIDIA nvcomp, NVIDIA Distributed join, NVIDIA cuCollections .

NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and dedicated people in the world working for us. If you're creative and autonomous, we want to hear from you.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 124,000 USD - 195,500 USD for Level 2, and 152,000 USD - 241,500 USD for Level 3.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 6, 2026.

This posting is for an existing vacancy. 

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering a diverse work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

#deeplearning

What you'll do

1Research and develop techniques to GPU-accelerate high-performance database, ETL, and data analytics applications
2Perform in-depth analysis and optimization of complex data-intensive workloads for GPU architectures
3Work directly with technical experts in industry and academia on performance optimization
4Influence the design of next-generation hardware architectures, software, and programming models
5Collaborate cross-functionally with research, hardware, system software, libraries, and tools teams at NVIDIA
6Contribute to open-source GPU-accelerated computing projects such as nvcomp, cuCollections, and Distributed Join

Requirements

Masters or PhD in Computer Science, Computer Engineering, or related computationally focused field
Strong C/C++ programming fluency with deep understanding of algorithms and software design
Hands-on experience with low-level parallel programming frameworks such as CUDA, OpenMP, MPI, or pthreads
In-depth expertise with CPU/GPU architecture fundamentals, especially memory subsystems
Domain expertise in high-performance databases, ETL, data analytics, and/or vector databases

Nice to have

CUDA kernel profiling and optimization
Database operator or query planner optimization for parallel/distributed frameworks
Vector database index build and search optimization
Experience with Spark or production database frameworks
Background in compression, storage systems, networking, and distributed architectures

Role overview

Role family
Developer Technology Engineering
Level
IC2 — ml_ai
Experience
0–2 years
Type
Individual Contributor
Remote policy
On-site
Visa sponsorship
Available

Tech stack analysis

LANGUAGES
CC++CUDA
FRAMEWORKS
OpenACCOpenMPMPIpthreadsTBBApache Spark
DATABASES
High-performance relational databasesVector databases
INFRASTRUCTURE
Multi-GPU systemsDistributed computing clustersNVIDIA GPU hardware
TOOLS
NVIDIA nvcompNVIDIA cuCollectionsNVIDIA Distributed JoinCUDA profiling tools

Green flags

5 items
Salary range fully disclosed with two level bands ($124K–$195.5K for L2, $152K–$241.5K for L3), plus equity — strong transparency for a new grad rolecompensation

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Benefits breakdown

HEALTH & WELLNESS
Benefits package mentioned (details not specified)

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Hiring insights

JD quality
8/10
Urgency
medium
Autonomy
high
Team size
small (2-5)

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Red flags

PRO3 items
Expecting Masters or PhD candidates with deep CPU/GPU architecture expertise, CUDA proficiency, AND database domain knowledge — very broad requirement set for a 'new grad' rolerequirements

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Interview insights

PRO
Rounds
5
Duration
4 wks
Difficulty
very hard
Take-home
No

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Career path

PRO
Next roles
Senior Developer Technology EngineerGPU Software EngineerPrincipal Research Scientist (HPC/Databases)

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About the company

NVIDIA is the world's leading designer of GPUs and AI computing platforms. Its chips power everything from gaming and data centers to autonomous vehicles and scientific research. With a market cap exceeding $2 trillion, NVIDIA's CUDA platform and AI accelerators have become the backbone of the global AI revolution.

HQSanta Clara, CA, USA
Interview difficultyvery hard
Build vs Maintainbuild
Cross-functionalYes