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Online Nvidia Engineering Jobs (NOW HIRING)

Nvidia

OR · On-site

$102K - $134K/yr

Join our DRIVE Road Structure, Online Mapping, and Context Fusion team and lead the development of ... In this role, you will partner with cross-functional engineering leaders to architect and deliver ...

Nvidia

OR · On-site

$104K - $137K/yr

We are looking for a strong engineer in the DRIVE Road structure / Online mapping / Context Fusion ... NVIDIA is widely considered to be one of the technology world's most desirable employers with some ...

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Online Nvidia Engineering information

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$46.5K

$146.9K

$174K

How much do online nvidia engineering jobs pay per year?

As of Jun 16, 2026, the average yearly pay for online nvidia engineering in the United States is $146,868.00, according to ZipRecruiter salary data. Most workers in this role earn between $116,500.00 and $173,000.00 per year, depending on experience, location, and employer.

How much do NVIDIA engineers make?

NVIDIA engineers typically earn an average salary ranging from $80,000 to over $150,000 annually, depending on experience, location, and specific role. Senior positions, specialized skills, and advanced certifications can lead to higher compensation, especially in high-demand areas like AI and graphics processing. Entry-level engineers may start at lower salaries but have opportunities for growth with experience and skill development.

Can you work for NVIDIA remotely?

Online Nvidia Engineering roles often offer remote work options, depending on the specific position and team requirements. Candidates typically need strong technical skills, relevant certifications, and the ability to collaborate virtually using tools like VPNs and communication platforms. Availability of remote work varies by role and location policies.

What are some common challenges faced by engineers working in online Nvidia engineering roles, and how can they be addressed?

Engineers in online Nvidia roles often encounter challenges such as optimizing performance for GPU-accelerated applications in cloud environments, ensuring security and scalability, and integrating with rapidly evolving technologies. Collaboration across distributed teams and effective communication are key to addressing these challenges. Staying updated with Nvidia’s latest frameworks and participating in peer code reviews can also help engineers adapt to changes and maintain high-quality standards.

What are Online Nvidia Engineers?

Online Nvidia Engineers are professionals who develop, maintain, and optimize software, systems, or platforms that leverage Nvidia technologies, particularly in cloud or online environments. They often work with Nvidia GPUs, CUDA, and related frameworks to accelerate computing tasks, support AI and machine learning workloads, and ensure high performance for online applications. These engineers collaborate with software developers, data scientists, and IT teams to deploy scalable solutions that utilize Nvidia hardware and software, often in data centers or cloud infrastructures.

What is the difference between Online Nvidia Engineering vs Online Nvidia Data Scientist?

AspectOnline Nvidia EngineeringOnline Nvidia Data Scientist
Required CredentialsBachelor's in Engineering, Computer Science, or related field; experience with GPU architecturesBachelor's or Master's in Data Science, Statistics, or related; knowledge of machine learning
Work EnvironmentCollaborative teams, remote or on-site, focusing on hardware and software developmentData analysis, model development, often remote, focusing on data insights and algorithms
Employer & Industry UsageTech companies, hardware manufacturers, AI research labsTech firms, AI companies, research institutions

Online Nvidia Engineering primarily involves designing and developing GPU hardware and related software, requiring engineering credentials. In contrast, Online Nvidia Data Scientists focus on analyzing data, building models, and deriving insights, requiring data science expertise. Both roles are integral to Nvidia's AI and tech ecosystem but differ in focus and skill set.

What are the key skills and qualifications needed to thrive as an Online Nvidia Engineer, and why are they important?

To thrive as an Online Nvidia Engineer, you need a strong background in computer engineering, programming (especially C++ and Python), and a deep understanding of GPU architectures, often with a relevant degree in computer science or electrical engineering. Familiarity with Nvidia software stacks like CUDA, TensorRT, and development tools such as Git, Jenkins, and cloud platforms is typically required, along with certifications like Nvidia Deep Learning Institute credentials. Exceptional problem-solving, collaboration, and communication skills help you excel in cross-functional teams and adapt to fast-evolving technologies. These skills are critical for creating innovative, high-performance solutions and ensuring the reliability and scalability of Nvidia's online systems.

Is it difficult to get hired at NVIDIA?

Getting hired as an online Nvidia engineer can be competitive, as the company seeks candidates with strong technical skills, relevant experience, and often advanced degrees in engineering or computer science. The hiring process typically involves multiple interviews, technical assessments, and a review of project portfolios or coding skills. Candidates who demonstrate proficiency with GPU architecture, programming languages like C++ or Python, and familiarity with AI or deep learning tools tend to have better chances.

Which engineers are hired by NVIDIA?

NVIDIA hires a variety of engineers including hardware engineers, software engineers, AI and deep learning engineers, and systems engineers. These roles often require expertise in programming languages such as C++ and Python, knowledge of GPU architecture, and experience with machine learning frameworks. Candidates typically need a relevant degree and experience in their specialized field.
What cities are hiring for Online Nvidia Engineering jobs? Cities with the most Online Nvidia Engineering job openings:
What are the most commonly searched types of Nvidia Engineering jobs? The most popular types of Nvidia Engineering jobs are:
What states have the most Online Nvidia Engineering jobs? States with the most job openings for Online Nvidia Engineering jobs include:
Online Nvidia Engineering jobs near you
Senior Software Systems Engineer, L3 and L4 - Autonomous Driving

Senior Software Systems Engineer, L3 and L4 - Autonomous Driving

Nvidia Corporation

Santa Clara, CA • On-site

Full-time

Posted 13 days ago

Job description

Today, NVIDIA is tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU serves as the intelligence behind computers, robots, and autonomous vehicles that perceive the world. Doing what's never been done before takes vision, innovation, and the world's best talent. We pioneered a supercharged form of computing loved by the most demanding computer users in the world - scientists, designers, artists, and gamers. It's not just technology though! It is our people, some of the brightest in the world, and our diverse company culture make NVIDIA one of the most fun, innovative and dynamic places to work in the world! At the center of NVIDIA's culture are our core values like innovation, excellence and determination and team, that guide us to be the best we can be. As an NVIDIAN, you'll be immersed in a diverse, encouraging environment where everyone is motivated to perform at their highest level. Come join the team and see how we can make a lasting impact on the world.
What you'll be doing:
  • Develop use cases and system requirements for L3 and L4 autonomous driving products based on customer needs, traffic regulations, certification standards, and industry guidelines.
  • Perform system-level analysis to define performance requirements and allocate performance budgets across subsystems.
  • Formulate test cases and define critical performance metrics to ensure compliance with functional and safety requirements.
  • Define and drive online and offline test strategy and execution at both vehicle and component levels.
  • Partner closely with Data Analytics, Test Engineering, and System Integration & Test teams. Ensure the right evaluators and important metrics are developed. Prove that datasets cover sufficient scenarios and requirements. Target appropriate sampling strategies through Data Collection and Real-World Driving.
  • Establish strong multi-functional relationships with collaborators across engineering, safety, validation, and product teams.
  • Drive innovation in requirements decomposition, traceability, and verification processes.
  • Promote and cultivate a strong systems engineering approach across the organization.

What we need to see:
To succeed in this role, you should have:
  • MS or PhD in Engineering, Physics, Computer Science, or a related field (or equivalent experience).
  • 8+ years proven experience in safety-critical systems engineering, system analysis, data analysis, and software architecture.
  • Strong software development background with proven coding skills.
  • Hands-on experience in SOTIF analysis (ISO 21448), functional safety (ISO 26262), and multi-functional architectural trade-off analysis.
  • Strong leadership and interpersonal skills, with the ability to drive alignment across large organizations.
  • Proven understanding of trade-offs between End-to-End deep learning approaches, classical modular perception/planning stacks, and associated validation and test strategies.

Ways to Stand Out from the crowd:
  • Experience contributing to a launched L3/L4 autonomous vehicle program.
  • Experience in AI safety and safety validation for ML-based systems.
  • Hands-on experience with large-scale datasets, data science, and analytics workflows.
  • Strong software engineering experience with proficiency in Python, SQL, and C++.

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until April 17, 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

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