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Remote Nvidia Hardware Engineer Jobs in Texas (NOW HIRING)

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

CUDA Developer - Remote

Houston, TX · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

CUDA Developer - Remote

Austin, TX · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

CUDA Developer - Remote

Dallas, TX · Remote

$60 - $100/hr

CUDA Engineering Expert Job Type: Contractor Location: Remote Job Overview We are seeking ... Experience using GPU profiling tools such as NVIDIA Nsight or similar. * Strong understanding of ...

... NVIDIA/AMD GPU device plugins and Kubernetes Operators to expose hardware capabilities to the ... Collaborate with the Scheduling and Storage engineering teams to ensure topology-aware placement ...

... Nvidia Fellow, the Head of Optics at Google, and many other industry leaders. Our work is guided by ... Ability to work across hardware and software teams and translate workload behavior into ...

... hardware security, AIdriven resilience and efficiency, and realtime platform management. Our ... NVIDIA, Intel, and AMD-based systems to enhance AI-driven functionality. 6. Develop and maintain ...

... hardware on the manufacturing line, to custom tooling to stream neural recordings from implants ... This includes remote caching, remote execution, target identification and selection, etc. * Operate ...

Showing results 21-40

Remote Nvidia Hardware Engineer information

What does a remote Nvidia hardware engineer do?

A Remote Nvidia Hardware Engineer focuses on designing, developing, and testing hardware components and systems for Nvidia products, such as graphics processing units (GPUs) and related technologies, while working from a remote location. They collaborate with cross-functional teams to ensure hardware solutions meet performance, reliability, and efficiency standards. Their work may include circuit design, board layout, hardware debugging, and supporting the integration of Nvidia hardware into various devices. Remote engineers use digital communication and collaboration tools to work effectively with global teams and contribute to innovative hardware solutions.

What are the key skills and qualifications needed to thrive as a remote Nvidia hardware engineer, and why are they important?

To thrive as a Remote Nvidia Hardware Engineer, you need a strong background in electrical or computer engineering, experience with GPU architecture, and proficiency in hardware design and validation. Expertise with tools such as Verilog/VHDL, simulation environments, and familiarity with Nvidia’s development platforms or relevant certifications is common. Strong problem-solving abilities, effective remote communication, and collaborative teamwork skills set top candidates apart. These competencies ensure efficient development, troubleshooting, and innovation in high-performance hardware solutions within distributed teams.

What are some common challenges faced by remote Nvidia hardware engineers, and how can they be addressed?

Remote Nvidia Hardware Engineers often encounter challenges related to effective collaboration and communication, especially when working on complex hardware design and testing with distributed teams. Staying aligned with project milestones, ensuring access to necessary hardware resources, and troubleshooting remotely can also be demanding. These challenges can be addressed by leveraging robust collaboration tools, maintaining clear documentation, and scheduling regular virtual meetings to synchronize efforts. Additionally, using remote desktop solutions and cloud-based simulation environments can help bridge the gap when physical access to hardware is limited.

What is the difference between Remote Nvidia Hardware Engineer vs Remote Nvidia Software Engineer?

AspectRemote Nvidia Hardware EngineerRemote Nvidia Software Engineer
Required CredentialsBachelor's or higher in Electrical Engineering, Computer Engineering, or related; hardware design certificationsBachelor's or higher in Computer Science, Software Engineering, or related; programming certifications
Work EnvironmentDesigning and testing hardware components, collaborating with hardware teamsDeveloping software, drivers, and algorithms for Nvidia products
Industry UsageHardware development for GPUs, AI accelerators, and embedded systemsSoftware development for drivers, SDKs, and AI frameworks

The main difference is that Remote Nvidia Hardware Engineers focus on designing and testing physical hardware components, while Remote Nvidia Software Engineers develop the software that runs on Nvidia hardware. Both roles require technical expertise but differ in their focus areas within the Nvidia ecosystem.

What are the most commonly searched types of Nvidia Hardware Engineer jobs in Texas?

The most popular types of Nvidia Hardware Engineer jobs in Texas are:

What are popular job titles related to Remote Nvidia Hardware Engineer jobs in Texas?

For Remote Nvidia Hardware Engineer jobs in Texas, the most frequently searched job titles are:

What job categories do people searching Remote Nvidia Hardware Engineer jobs in Texas look for?

The top searched job categories for Remote Nvidia Hardware Engineer jobs in Texas are:

What cities in Texas are hiring for Remote Nvidia Hardware Engineer jobs?

Cities in Texas with the most Remote Nvidia Hardware Engineer job openings:

CUDA Engineering Expert - Remote

YO AI Labs

Dallas, TX • Remote

$60 - $100/hr

Full-time

Posted 12 days ago


Job description

CUDA Engineering Expert

Job Type: Contractor
Location: Remote

Job Overview

We are seeking experienced CUDA Engineering Experts to support a cutting-edge GPU optimization project. You will apply your expertise in CUDA, C++, and GPU programming to analyze, optimize, and improve high-performance GPU kernels.

No prior AI experience is required.

Key Responsibilities
  • Analyze, profile, and optimize GPU kernels using CUDA and profiling tools.

  • Identify performance bottlenecks and develop targeted optimization strategies.

  • Refactor C++ and CUDA code for efficiency and maintainability.

  • Develop shader logic using GLSL and WebGPU.

  • Document optimization processes, findings, and performance improvements.

  • Contribute to GPU architecture and performance discussions.

  • Collaborate with remote, cross-functional teams.

Required Qualifications
  • Strong expertise in CUDA programming and GPU kernel optimization.

  • Advanced C++ development skills.

  • Hands-on experience with GLSL and WebGPU.

  • Experience using GPU profiling tools such as NVIDIA Nsight or similar.

  • Strong understanding of GPU performance and architecture.

  • Excellent analytical, problem-solving, and technical communication skills.

  • Ability to work effectively in a remote environment.

Preferred Qualifications
  • Experience with high-performance computing or GPU-accelerated applications.

  • Experience optimizing workloads across different GPU architectures.

  • Background in graphics, compute shaders, or AI/ML acceleration.