ZipRecruiter

Log In

1

Internship Nvidia Hardware Engineer Jobs in Colorado

Nvidia

Principal CPU Software Architect

Boulder, CO

NVIDIA is developing processor and system architectures that are at the forefront of accelerating ... What you'll be doing: * Collaborate with Hardware and Software Engineers to craft the next ...

Nvidia

HPC Middleware Developer

Boulder, CO

We are now looking for a senior HPC software engineer. As a member of our the High Performance ... Our team works closely with networking chip design teams in co-designing new hardware features and ...

next page

Showing results 1-20

All JobsNvidia Hardware Engineer JobsInternship Nvidia Hardware Engineer JobsInternship Nvidia Hardware Engineer Jobs in Colorado

Internship Nvidia Hardware Engineer information

What does an internship Nvidia hardware engineer do?

An Internship Nvidia Hardware Engineer works alongside experienced engineers to assist in designing, testing, and validating hardware components such as GPUs, processors, and related systems. Interns typically get hands-on experience with circuit design, simulation, debugging, and performance analysis. They may also collaborate with cross-functional teams to optimize hardware for efficiency and performance. This role gives students exposure to industry-standard tools and real-world engineering challenges, preparing them for future careers in hardware engineering.

What are the key skills and qualifications needed to thrive as an internship Nvidia hardware engineer?

To thrive as an Internship Nvidia Hardware Engineer, you need a solid understanding of electrical engineering fundamentals, digital/analog circuit design, and relevant coursework or project experience. Familiarity with hardware description languages (such as Verilog or VHDL), simulation tools (like ModelSim or Cadence), and version control systems is typically expected. Strong problem-solving abilities, effective teamwork, and clear communication distinguish top candidates in this role. These skills and qualities are crucial to efficiently contribute to complex hardware development projects and collaborate within multidisciplinary engineering teams.

What kinds of projects can an intern expect to work on as a hardware engineer at Nvidia?

As a Hardware Engineer intern at Nvidia, you can expect to be involved in hands-on projects that support the development, testing, and validation of hardware components such as GPUs, system boards, or AI accelerators. Interns often collaborate closely with experienced engineers, contributing to tasks like schematic reviews, board bring-up, signal integrity analysis, or automation of testing procedures. These projects provide opportunities to learn industry-standard tools and workflows, as well as gain practical experience in problem-solving and cross-functional teamwork. This exposure not only builds technical skills but also helps interns understand the end-to-end hardware development lifecycle.

What is the difference between Internship Nvidia Hardware Engineer vs Nvidia Hardware Engineer?

AspectInternship Nvidia Hardware EngineerNvidia Hardware Engineer
QualificationsEnrolled in a relevant degree program, some technical courseworkBachelor's or Master's in Electrical Engineering, Computer Engineering, or related fields
Work EnvironmentInternship program, mentorship, collaborative teamsFull-time, professional environment, project ownership
ResponsibilitiesAssist in hardware design, testing, and documentationDesign, develop, and optimize hardware components and systems

Internship Nvidia Hardware Engineers are students gaining practical experience, focusing on learning and assisting with hardware projects. Nvidia Hardware Engineers are full-time professionals responsible for designing and developing advanced hardware solutions. The internship offers a pathway to a career in hardware engineering, while full-time roles involve more responsibility and expertise.

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

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

What are popular job titles related to Internship Nvidia Hardware Engineer jobs in Colorado?

For Internship Nvidia Hardware Engineer jobs in Colorado, the most frequently searched job titles are:

What job categories do people searching Internship Nvidia Hardware Engineer jobs in Colorado look for?

The top searched job categories for Internship Nvidia Hardware Engineer jobs in Colorado are:

What cities in Colorado are hiring for Internship Nvidia Hardware Engineer jobs?

Cities in Colorado with the most Internship Nvidia Hardware Engineer job openings:

Internship Nvidia Hardware Engineer jobs near you
Infographic showing various Internship Nvidia Hardware Engineer job openings in Colorado as of July 2026, with employment types broken down into 92% Full Time, 4% Part Time, and 4% Contract. Highlights an 89% Physical, 4% Hybrid, and 7% Remote job distribution.

Senior Edge AI Perception Engineer

AION ROBOTICS CORPORATION

Arvada, CO • On-site

$107K - $147K/yr

Full-time

Re-posted 28 days ago

Job description

Job Summary:
AION Robotics Corporation is a rapidly growing startup manufacturing advanced autonomous ground vehicles for critical infrastructure monitoring. They are seeking a highly skilled Senior Edge AI Perception Engineer to design, optimize, and deploy deep learning models for real-time autonomous vehicle perception systems.
Responsibilities:
• Neural Network Model Development & Optimization
• Build and manage optimized neural network pipelines tailored for edge deployment in autonomous vehicle systems.
• Implement, compress, and optimize models (pruning, quantization, scheduling) to run on GPU, DLA, and Tensor cores.
• Work with architectures including monocular depth models, YoloX, PeopleNet, ResNet, and others.
• Leverage NVIDIA DeepStream, TensorRT, CUDA, and TAO Toolkit to create high-performance perception pipelines.
• Manage model/hardware resource allocation across GPU/DLA for real-time scheduling and execution.
• Optimize pipelines “lens-to-detections” meeting ultra-low latency constraints on embedded devices such as NVIDIA Orin & Thor.
• Apply real-time geometric transforms to object detections and semantic segmentation results for geo-referencing and LiDAR point cloud filtering.
• CUDA accelerated 3D Terrain mapping
• Develop and maintain automated data collection pipelines, including dataset formatting, labeling workflows (CVAT), and fine-tuning for custom training.
• Implement real-time dewarped camera pipelines using GMSL drivers, VIC, and ARGUS APIs on embedded platforms.
• Collaborate with hardware engineers to achieve consistent calibration and synchronization across multiple sensors.
• Stay up to date with bleeding-edge advancements in neural networks, edge AI optimization, and autonomous perception.
• Rapidly prototype and validate new models and methods for production deployment.
Qualifications:
Required:
• Direct real-world experience in computer vision, deep learning, or edge AI systems.
• Strong proficiency with CUDA, TensorRT, NVIDIA DeepStream, TAO Toolkit, PyTorch/TensorFlow.
• Demonstrated experience with model optimization techniques (e.g., pruning, quantization, distillation, scheduling).
• Hands-on experience deploying AI pipelines to embedded edge platforms (preferably NVIDIA Jetson Orin or Thor).
• Expertise in object detection, semantic segmentation, and depth estimation.
• Solid understanding of real-time embedded system constraints and low-latency optimization strategies.
• Strong programming skills in C++ and Python.
Preferred:
• Experience with low-level camera system integration, including ISP tuning, intrinsic & extrinsic calibration algorithms, multi-camera synchronization and fusion.
• Familiarity with sensor fusion pipelines combining camera, LiDAR, and IMU.
• Direct experience working in autonomous vehicles, robotics, ROS2 or safety-critical perception systems.
Company:
Our rugged autonomous vehicles bring Industry 4.0 to outdoor commercial jobsites through the automation of infrastructure monitoring, maintenance and inspection tasks. Founded in 2016, the company is headquartered in Denver, USA, with a team of 11-50 employees. The company is currently Early Stage.

Apply