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Nvidia Machine Learning Jobs in California (NOW HIRING)

... Nvidia, TRI, etc.). * Technical : Expertise in training machine learning models, including deep ... learning, reinforcement learning or genetic algorithms. This does not include building multi-agent ...

Job Requisition ID JR2021784 Job Category Engineering Time Type Full time NVIDIA is in a unique ... We are looking for a talented Machine Learning Engineer to work on Product Security, Content Safety ...

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

3D Machine Learning Engineer

Irvine, CA · On-site

$150K - $200K/yr

What You'll Do * Design and implement scalable machine learning pipelines for large-scale 3D ... We bring deep experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA ...

Showing results 21-40

Nvidia Machine Learning information

What is a Nvidia machine learning job?

A Nvidia Machine Learning job involves developing and optimizing AI models, deep learning frameworks, and GPU-accelerated applications. Engineers in this role work on cutting-edge research, building scalable ML solutions, and improving performance on Nvidia hardware like GPUs and AI accelerators. They collaborate with software and hardware teams to enhance AI capabilities across industries such as gaming, healthcare, and autonomous systems. Strong coding skills in Python, C++, and experience with ML frameworks like TensorFlow or PyTorch are often required.

What are the key skills and qualifications needed to thrive in the Nvidia machine learning position?

To thrive in an Nvidia Machine Learning role, a deep understanding of machine learning algorithms, proficiency in programming languages like Python or C++, and a solid background in mathematics or computer science are essential. Experience with Nvidia's CUDA, TensorRT, cuDNN, and familiarity with modern deep learning frameworks such as TensorFlow or PyTorch are highly valued, as are relevant certifications in AI or data science. Strong problem-solving skills, teamwork, and effective communication distinguish top candidates in collaborative, fast-paced environments. These skills are crucial for developing and optimizing AI solutions that leverage Nvidia’s advanced hardware and software platforms.

What are some common challenges faced by professionals in Nvidia machine learning roles?

One common challenge in Nvidia Machine Learning roles is optimizing models to fully leverage GPU architectures for both performance and efficiency, which requires continuous learning as the technology rapidly evolves. Team members often work on complex, large-scale projects that demand close collaboration across software, hardware, and research divisions. Navigating the fast pace of innovation and contributing effectively to cross-functional teams is essential for success. However, these challenges also make the role exciting and offer excellent opportunities for professional growth and hands-on experience with state-of-the-art AI solutions.

What are the most commonly searched types of Nvidia Machine Learning jobs in California?

The most popular types of Nvidia Machine Learning jobs in California are:

What job categories do people searching Nvidia Machine Learning jobs in California look for?

The top searched job categories for Nvidia Machine Learning jobs in California are:

What cities in California are hiring for Nvidia Machine Learning jobs?

Cities in California with the most Nvidia Machine Learning job openings:

Infographic showing various Nvidia Machine Learning job openings in California as of August 2026, with employment types broken down into 1% As Needed, 75% Full Time, 23% Part Time, and 1% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Machine Learning Engineer, Perception - Autonomous Driving

Nvidia

Santa Clara, CA • On-site

$122K - $168K/yr

Full-time

Re-posted 20 days ago


Nvidia rating

9.6

Company rating: 9.6 out of 10

Based on 18 frontline employees who took The Breakroom Quiz

6th of 247 rated software companies


Job description

Intelligent machines powered by Artificial Intelligence computers that can learn, reason and interact with people are no longer science fiction. GPU Deep Learning has provided the foundation for machines to learn, perceive, reason and solve problems. Now, NVIDIA's GPU runs 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.

We are now looking for an extraordinary Senior Perception Engineer to develop and productize NVIDIA's autonomous driving solutions. As a member of our perception team, you will be driving E2E solutions for perception modules that are responsible for online mapping - including road layouts, lane structures, boundaries, crosswalks, and other traffic components critical for driving without reliance on HD maps. You will be challenged to improve robustness and accuracy as well as efficiency of the solutions to fully enable autonomous driving anywhere and anytime.

What You'll Be Doing: Designing end2end solutions for Perception and AV stack to enable road network detections across various driving environments from complex intersections to rural curvy roads to multi-level highways. Applied research and development of innovative deep learning models for lane graph construction, road boundary detection, traffic element recognition, and other static-world tasks. Develop generalizable approaches to support diverse ODDs and Country/region expansion Drive and prioritize data-driven development by working with large data collection and labeling teams to bring in high value data to improve perception system accuracy.

Efforts will include data collection prioritization and planning, labeling prioritization, labeling efficiency optimization, so that value of data is maximized Leverage data simulation and augmentation for solving extreme scenarios Productize the developed perception solutions by meeting product requirements for safety, latency, and SW robustness. What We Need to See: Minimum Requirement: PhD with 4+ years, MS with 6+ years, or BS (or equivalent experience) with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field. 2+ years of technical leadership demonstrating high technical and organizational complexity is a big plus.

Hands-on work experience in developing deep learning and algorithms to solve sophisticated real world problems, and proficiency in using deep learning frameworks (e.g., PyTorch). Experience in data-driven development and collaboration with data and ground truth teams. Strong programming skills in python and/or C++

Outstanding communication and teamwork skills as we work as a tightly-knit team, always discussing and learning from each other. Ways to Stand Out from the Crowd: Proven expertise in developing generalizable perception solutions for autonomous driving or robotics using deep learning with cameras. Hands-on experience in developing and deploying DNN-based solutions to embedded platforms for real time applications.

Proven expertise in deep learning backed up by technical publications in leading conferences/journals. Expertise with Transformers, BEV architectures, and modern static-world perception techniques.Experience in working on similar online mapping and complex road detection problems is a big plus. Intelligent machines powered by AI are no longer science fiction

GPU Deep Learning has made it possible for self-driving cars to learn, perceive, and reason about the world. NVIDIA GPUs power the algorithms that enable both static world understanding and scalable perception across global road systems. Join us and help define the future of reliable, data-driven autonomous driving.

#AutonomousVehicles 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 September 2, 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.


What Nvidia employees say

Pay

Benefits

Hours and flexibility

Workplace

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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