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Data Labeling Nvidia Jobs (NOW HIRING)

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$104K - $143K/yr

Drive and prioritize data-driven development by working with large data collection and labeling ... NVIDIA GPUs power the algorithms that enable both static world understanding and scalable ...

Senior Vision Language Model Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

NVIDIA is the platform upon which every new AI-powered application is built. They are seeking a ... workflows that automate data discovery, labeling, evaluation, and retraining to maximize ...

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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 Manager, Machine Learning Ops Engineering - Automotive

Senior Manager, Machine Learning Ops Engineering - Automotive

Nvidia

Santa Clara, CA

Full-time

Posted 17 days ago


Job description

NVIDIA is seeking a Senior MLOps Engineering Manager to join our Autonomous Driving organization in Santa Clara, CA. This role offers an outstanding opportunity to lead the build, development, and operation of largescale, endtoend data and ML pipelines that power NVIDIA's autonomous driving products. You will lead a highly technical engineering team responsible for building and operating cloudscale pipelines that ingest, validate, process, and transform extensive volumes of multimodal sensor data-including camera, lidar, and radar-into highquality training, evaluation, and validation datasets. These pipelines are foundational to NVIDIA's AV program and directly enable customerfacing autonomy features. We want a seasoned engineering leader with strong ownership and passion for customerfocused development. This person will scale systems and teams in a fast paced, multifunctional environment.

What You Will Be Doing:

  • Lead and grow a highperforming MLOps engineering group tasked with managing endtoend data pipelines supporting NVIDIA's autonomous driving technology from levels L2 through L4.

  • Own the architecture, execution, and operational excellence of largescale, cloudnative pipelines for multimodal sensor data ingestion, processing, labeling, and validation.

  • Drive the development of robust, scalable, and observable MLOps systems that support model training, ground truth generation, and continuous evaluation at AV scale.

  • Partner closely with perception, ML, data labeling, infrastructure, and product teams to translate customer and program requirements into reliable production systems.

  • Define technical vision, roadmap, success metrics, and operational benchmarks, and ensure consistent execution against program achievements.

  • Champion customerfirst thinking and ownership, ensuring the systems your team builds directly deliver measurable value to internal and external AV customers.

  • Balance handson technical depth with people leadership, providing technical guidance, mentorship, and career development for senior engineers and managers.

  • Operate across multiple layers of the stack, including Python, C++, distributed systems, cloud infrastructure, CI/CD, and data platforms.

What We Need to See:

  • Bachelor's or equivalent experience, Master's, or PhD in Computer Science, Electrical Engineering, or a closely related field (or equivalent experience).

  • 10+ overall years of overall engineering experience, including crafting and coordinating productiongrade distributed systems.

  • 5+ years of engineering management experience, with a proven history of guiding teams delivering sophisticated, largescale systems.

  • Strong background in MLOps, data pipelines, and cloudbased distributed systems.

  • Proficiency in Python and C++, with the ability to guide systemlevel and performancecritical build decisions.

  • Experience crafting and operating endtoend data or ML pipelines with high reliability, scale, and observability.

  • Prior experience in one or more of the following domains: Autonomous Vehicles, Robotics, Computer Vision, Deep Learning, or GPUaccelerated computing.

  • Excellent communication and leadership skills, capable of aligning collaborators and driving execution in a multi-functional organization.

  • Demonstrated passion for ownership, accountability, and engineering that prioritizes customers.

Ways to Stand Out from the Crowd:

  • Experience developing and leading AVscale data platforms handling petabytescale sensor data.

  • Strong background of leading teams responsible for production MLOps or data infrastructure.

  • Experience with automotive or robotic systems, including realworld sensor data pipelines.

  • Background in distributed cloud systems, workflow orchestration, and largescale CI/CD.

  • Familiarity with 3D geometry, perception pipelines, or data generation based on simulated environments.

NVIDIA is widely considered one of the most sought-after employers in the technology industry. We offer highly competitive compensation along with an extensive benefits plan. Our work enables new universes of discovery-from artificial intelligence to autonomous vehicles-and brings oncesciencefiction technologies into reality. If you are passionate about autonomous driving, scaling complex systems, and leading teams that deliver real customer impact, we would love 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 272,000 USD - 431,250 USD.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until March 27, 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.

Nvidia logo

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