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Data Labeling Nvidia Jobs (NOW HIRING)

Navstar

Machine Learning Engineer

Centreville, VA

$102K - $144K/yr

Perform visual imagery data science to inform data collection, data labeling, and data selection ... Familiarity with Nvidia Tools (CUDA, JetPack, TensorRT) and deployment process to Nvidia GPUs

AST SpaceMobile

AI Lab Manager

Midland, TX · On-site

Prior experience supporting computer vision, machine learning, or data-labeling operations ... Experience administering GPU workstations or servers (NVIDIA driver / CUDA toolchains) * Background ...

HPTech Inc.

Data Center Technician

Reno, NV

Make sure that all cables ran are bundled neatly and in accordance with Nvidia''s standard ... copper) including labeling and cable management Support installation, relocation, and ...

Omni Inclusive

L1 Data Center Technician

Reno, NV

... with Nvidia's standard. • Double-check with network admins to make sure everything is cabled ... copper), including labeling and cable management Support installation, relocation, and ...

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Data Labeling Nvidia information

Is data labelling a good career?

Data labeling is a foundational role in machine learning and AI development, involving annotating data to improve model accuracy. It often requires attention to detail, basic technical skills, and can offer entry-level opportunities with flexible schedules. While it can be a stepping stone to more advanced roles in data science or AI, it may have limited career growth without additional skills or experience.

What are the key skills and qualifications needed to thrive as a Data Labeling Specialist at Nvidia, and why are they important?

To succeed as a Data Labeling Specialist at Nvidia, you need attention to detail, basic data analysis skills, and familiarity with data annotation processes, typically supported by a relevant degree or experience in data handling. Proficiency with data labeling platforms, annotation tools, and sometimes scripting languages like Python is often required. Strong organizational skills, reliability, and the ability to follow detailed instructions are essential soft skills for this role. These skills ensure high-quality, accurate datasets that are crucial for training and validating AI models used in Nvidia’s cutting-edge technologies.

What is the difference between Data Labeling Nvidia vs Data Annotation Specialist?

AspectData Labeling NvidiaData Annotation Specialist
CredentialsBasic technical skills, familiarity with AI toolsSimilar credentials, often with some technical background
Work EnvironmentTech companies, AI/ML teams, remote or on-siteTech firms, research labs, remote or on-site
Industry UsagePrimarily in AI hardware and software developmentAcross AI, machine learning, and data processing industries

Data Labeling Nvidia focuses on preparing data for AI models, often within Nvidia's ecosystem, while Data Annotation Specialists perform similar tasks across various companies. Both roles require technical skills and are integral to AI development, but Data Labeling Nvidia is more specialized within Nvidia's hardware and software context.

What is data labeling at Nvidia?

Data labeling at Nvidia involves annotating or tagging data such as images, videos, or audio to train artificial intelligence and machine learning models. This process is crucial because accurately labeled data helps improve the performance of AI models used in applications like autonomous vehicles, robotics, and computer vision. Data labelers at Nvidia may use specialized software tools to mark objects, classify scenes, or provide other relevant information, ensuring the data is both high-quality and consistent. The work typically requires attention to detail and the ability to understand labeling guidelines specific to Nvidia's projects.

What are some common challenges faced by data labeling specialists at Nvidia, and how are they addressed within the team?

Data labeling specialists at Nvidia often encounter challenges such as ensuring high accuracy when annotating complex or ambiguous data, maintaining consistency across large datasets, and meeting tight project deadlines. To address these challenges, Nvidia provides robust training, utilizes specialized annotation tools, and encourages collaboration through regular team check-ins and quality audits. Team members frequently review each other's work to uphold standards and share best practices, fostering a supportive environment for continuous improvement.
Infographic showing various Data Labeling Nvidia job openings in the United States as of May 2026, with employment types broken down into 76% Full Time, 6% Part Time, 3% Temporary, and 15% Contract. Highlights an 85% In-person, and 15% Remote job distribution.
Senior Deep Learning and Computer Vision Engineer - Autonomous Vehicles

Senior Deep Learning and Computer Vision Engineer - Autonomous Vehicles

Nvidia

Redmond, WA

Full-time

Posted 9 days ago

Job description

We are looking for a Deep Learning and Computer Vision engineer for our Autonomous Vehicles team. The role involves applying state-of-the-art techniques to build ground truth for autonomous vehicles, a critical aspect of our next-generation products. You will have the opportunity to work with top researchers and engineers in the field of deep learning and computer vision to deliver impact to our customers around the world. Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer a science fiction. Today, a self-driving car powered by AI can meander through a country road at night and find its way. An AI-powered robot can learn motor skills through trial and error. The era of AI has begun. NVIDIA's GPUs run Deep Learning algorithms, simulating human intelligence, and acts as the brain of computers, robots and self-driving cars that can perceive and understand the world. Just as human imagination and intelligence are linked, computer graphics and AI come together in our architecture. This may explain why.

NVIDIA GPUs are used broadly for Deep Learning, and NVIDIA is increasingly known as "the AI company". Make your choice to join us today. We are training Deep Neural Networks for NVIDIA's Autonomous Vehicles effort, with the goal to enable autonomous driving. We are seeking Deep Learning/Machine Learning interns who are passionate about solving problems in perception, prediction, planning and control for self-driving cars to achieve full autonomy. Are you interested in inventing human level AI for navigation in the unconstrained world under any conditions? If so, join us!

What you'll be doing:

  • Stay up to date with the latest research and innovations in deep learning, implement and experiment with new ideas.

  • Foster collaborative partnerships with our researchers and engineers, transforming innovative research into robust, industrial-strength machine learning models.

  • Taking approaches from initial evaluation and experimentation all the way to shipping.

  • Defining and collecting training datasets.

  • Building training pipelines and real-time inference run-times (PyTorch, TensorFlow, TensorRT, Python, C++).

What we need to see:

  • PhD with 1+ year, or MS (or equivalent experience) with 5+ years, of relevant experiencein Computer Science, ComputerEngineering, or a related technical field.

  • Proven experience building robust software.

  • Passionate about Artificial Intelligence for robotics and autonomous navigation

  • Strive to learn new things and like solving hard problems

  • Math knowledge

  • Experience in Deep Learning / Machine Learning. You have a background in Computer vision and/or Planning/Control.

  • Programming and debugging skills in C++ and/or Python.

  • Good communication and analytical skills. Ability to work with multiple teams in a dynamic environment.

Ways to stand out from the crowd:

  • Background in applying latest AI methods to solve Computer Vision and Autonomous Vehicles problems

  • Experience with Unsupervised or Self-supervised Learning

  • Involvement with architecture optimization, pruning, curriculum & multi-task training

  • Experience fusing data from different sensor modalities (e.g. Images and LIDAR data) to enable information conflation, label propagation, cross training.

We believe that realizing self-driving cars will be a defining contribution of our generation. We have the funding and scale, but we need your help. NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most brilliant and talented people in the world working for us and, due to unprecedented growth, our world-class engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, 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 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until June 12, 2026.

This posting is for an existing vacancy.

NVIDIA uses AI tools in its recruiting processes.

NVIDIA is committed to fostering an inclusive 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.
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About Nvidia

Sourced by ZipRecruiter

NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It's a unique legacy of innovation that's fueled by great technology--and amazing people. Today, we're tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what's never been done before takes vision, innovation, and the world's best talent.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1993

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