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Nvidia Deep Learning Jobs in California (NOW HIRING)

NVIDIA

Senior Deep Learning Software Engineer

Santa Clara, CA · Hybrid

$142K - $188K/yr

Collaborate with teams across NVIDIA to use performant kernel implementations within the automated ... Familiarity with NVIDIA's deep learning SDKs such as TensorRT. * Prior experience in writing high ...

Nvidia

Senior Deep Learning Software Engineer

Santa Clara, CA · Hybrid

$143K - $189K/yr

Collaborate with teams across NVIDIA to use performant kernel implementations within the automated ... Familiarity with NVIDIA's deep learning SDKs such as TensorRT. * Prior experience in writing high ...

Nvidia

Senior Deep Learning Engineer

Santa Clara, CA

$65 - $83.75/hr

At NVIDIA, we are at the forefront of advancing the capabilities of artificial intelligence. We are seeking an ambitious and forward-thinking senior deep learning engineer to contribute to the ...

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Nvidia Deep Learning information

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$10.9K

$82.8K

$138.2K

How much do nvidia deep learning jobs pay per year?

As of Jun 12, 2026, the average yearly pay for nvidia deep learning in California is $82,787.00, according to ZipRecruiter salary data. Most workers in this role earn between $71,100.00 and $137,200.00 per year, depending on experience, location, and employer.

How much does a NVIDIA deep learning performance architect make?

A NVIDIA deep learning performance architect typically earns between $120,000 and $180,000 annually, depending on experience, location, and specific responsibilities. The role often requires expertise in AI frameworks, GPU architecture, and performance optimization. Compensation may also include bonuses and stock options based on performance and company policies.

What is an Nvidia Deep Learning job?

An Nvidia Deep Learning job typically involves working with AI, machine learning, and deep learning technologies to develop, optimize, and deploy neural network models. Employees in these roles may work on GPU acceleration, AI frameworks like TensorFlow and PyTorch, and specialized hardware like NVIDIA GPUs and TensorRT. Positions can range from research scientists and software engineers to AI infrastructure specialists, focusing on improving model performance and scalability. These professionals contribute to cutting-edge AI applications in fields like autonomous vehicles, healthcare, and robotics.

Is ML a high paying job?

Machine learning (ML) roles, including those related to Nvidia deep learning, are generally well-paid due to high demand for specialized skills in AI, data analysis, and programming. Salaries vary based on experience, location, and certifications, but many ML positions offer competitive compensation compared to other tech roles.

What are the main challenges faced by professionals working in Nvidia Deep Learning roles?

Professionals in Nvidia Deep Learning positions often encounter challenges such as optimizing deep learning models to run efficiently on GPU architectures, keeping up with rapidly evolving AI frameworks, and troubleshooting complex system-level integration issues. They may also need to balance tight project deadlines with the demands of rigorous research and experimentation. Collaboration with interdisciplinary teams—such as software developers, data scientists, and hardware engineers—is common and essential to deliver robust solutions. Overcoming these challenges helps professionals stay at the forefront of innovation in the AI and deep learning industry.

How much does a deep learning engineer make at NVIDIA?

A deep learning engineer at NVIDIA typically earns between $100,000 and $150,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in AI and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options.

How hard is it to get hired at NVIDIA?

Getting hired at NVIDIA for deep learning roles can be competitive, often requiring strong technical skills in machine learning, deep learning frameworks, and programming languages like Python and C++. Candidates typically need relevant experience, a solid educational background, and a demonstrated ability to work on complex projects. The hiring process may include technical interviews, coding assessments, and behavioral evaluations.

What are the key skills and qualifications needed to thrive in the Nvidia Deep Learning position, and why are they important?

Excelling in an Nvidia Deep Learning role requires a strong background in computer science, machine learning, and mathematics, often supported by an advanced degree in a related field. Expertise in deep learning frameworks (such as TensorFlow or PyTorch), CUDA programming, and experience with Nvidia GPU hardware are typically expected, along with relevant certifications like Nvidia Deep Learning Institute credentials. Strong analytical thinking, problem-solving abilities, and effective teamwork distinguish top performers in this position. These skills are crucial to efficiently develop, optimize, and deploy deep learning models leveraging Nvidia technologies in cutting-edge applications.

What are the most commonly searched types of Nvidia Deep Learning jobs in California? The most popular types of Nvidia Deep Learning jobs in California are:
What are popular job titles related to Nvidia Deep Learning jobs in California? For Nvidia Deep Learning jobs in California, the most frequently searched job titles are:
What job categories do people searching Nvidia Deep Learning jobs in California look for? The top searched job categories for Nvidia Deep Learning jobs in California are:
What cities in California are hiring for Nvidia Deep Learning jobs? Cities in California with the most Nvidia Deep Learning job openings:
Nvidia Deep Learning jobs near you
Infographic showing various Nvidia Deep Learning job openings in California as of June 2026, with employment types broken down into 67% Full Time, and 33% Contract. Highlights an 100% In-person job distribution, with an average salary of $82,787 per year, or $39.8 per hour.
Senior Deep Learning Software Engineer - Autonomous Vehicles

Senior Deep Learning Software Engineer - Autonomous Vehicles

Nvidia

Santa Clara, CA

$143K - $189K/yr

Full-time

Posted 19 days ago

Job description

We are looking for outstanding Deep Learning Software Engineers to develop and productize NVIDIA's deep learning solutions in autonomous driving vehicles. As a member of our SolutionEngineering-AutomotiveMachine Learning team, you will apply ground breaking NVIDIA deep learning model training/inference software libraries for deployment on NVIDIA's hardware architecture. You will develop new deep learning architectures, train deep learning models, and compile and optimize DNN graphs. As a part of this role, you will be building a close technical relationship with our automotive partners during product development and coordinate with the architecture and software teams to develop the best solution for partners working on our platforms.

What you'll be doing:

  • Train, fine-tune, optimize and customize perception DNNs in low precision (FP16/INT8)

  • Apply sophisticated quantization of DNNs

  • Improve DNN architectures using ML algorithms on NVIDIA GPUs or DLAs

  • Continuously improve inference speed, accuracy and power consumption of DNNs

  • Stay up to date with the latest research and innovations in deep learning, implement and experiment with new insights to improve NVIDIA's automotive DNNs.

What we need to see:

  • MS or PhD degree in computer science, computer vision, computer architecture or equivalent experience in technical field

  • 5+ years of work experience in software development.

  • 2+ years of experience in developing or using deep learning frameworks (e.g. PyTorch, JAX, TensorFlow, ONNX, etc.)

  • Experience with solving a computer vision task using deep neural networks, such as object detection, scene parsing, image segmentation.

  • Strong Python and/or C/C++ programming skills

  • Proven technical foundation in CPU and GPU architectures, containers (nvidia-docker), numeric libraries, modular software design

  • Familiar with CNNs and Transformer architectures

  • Willing to take action and have strong analytical skills.

  • Strong time-management and organization skills for coordinating multiple initiatives, priorities and implementations of new technology and products into very sophisticated projects.

Ways to stand out from the crowd:

  • Experience with low precision inference, quantization, compression of DNNs

  • Experience with NVIDIA software libraries such as CUDA and TensorRT

  • Open source project ownership or contribution, healthy GitHub repositories, guiding and/or mentoring experience

NVIDIA is widely considered to be one of the technology world's most desirable employers. We have some of the most hard-working and dedicated people in the world working for us. If you're creative and passionate about developing technologies for autonomous driving, 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 14, 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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