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Nvidia Machine Learning Jobs in California (NOW HIRING)

Field AI

3D Machine Learning Engineer

Irvine, CA

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 ...

Fieldai

3D Machine Learning Engineer

Irvine, CA · On-site

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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA · On-site

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 ...

FieldAI

3D Machine Learning Engineer

Irvine, CA

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 ...

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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, and why are they important?

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 are popular job titles related to Nvidia Machine Learning jobs in California? For Nvidia Machine Learning jobs in California, the most frequently searched job titles are:
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What cities in California are hiring for Nvidia Machine Learning jobs? Cities in California with the most Nvidia Machine Learning job openings:
Nvidia Machine Learning jobs near you
Infographic showing various Nvidia Machine Learning job openings in California as of June 2026, with employment types broken down into 33% Full Time, 50% Contract, and 17% Nights. Highlights an 83% Physical, 8% Hybrid, and 9% Remote job distribution.
Physicist/Scientist Machine Learning

Physicist/Scientist Machine Learning

Applied Materials

Santa Clara, CA • On-site

$138K - $190K/yr

Full-time

Posted 23 days ago

Applied Materials rating

8.6

Company rating: 8.6 out of 10

Based on 54 frontline employees who took The Breakroom Quiz

23rd of 516 rated manufacturers

Job description

Who We Are
Applied Materials is a global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We design, build and service cutting-edge equipment that helps our customers manufacture display and semiconductor chips - the brains of devices we use every day. As the foundation of the global electronics industry, Applied enables the exciting technologies that literally connect our world - like AI and IoT. If you want to push the boundaries of materials science and engineering to create next generation technology, join us to deliver material innovation that changes the world.
What We Offer
Salary:
$138,000.00 - $190,000.00
Location:
Santa Clara,CA
You'll benefit from a supportive work culture that encourages you to learn, develop, and grow your career as you take on challenges and drive innovative solutions for our customers. We empower our team to push the boundaries of what is possible-while learning every day in a supportive leading global company. Visit our Careers website to learn more.
At Applied Materials, we care about the health and wellbeing of our employees. We're committed to providing programs and support that encourage personal and professional growth and care for you at work, at home, or wherever you may go. Learn more about our benefits.
We are seeking a highly motivated MS or PhD-level scientist or engineer to develop and apply machine learning-based models using data generated from multi-dimensional, high-performance computing (HPC) simulations. The successful candidate will work at the intersection of physics-based modeling, large-scale simulation, and modern AI/ML methods to accelerate product developing in the fast-paced semiconductor equipment industry. Focus will be on developing ML models based on plasma and electromagnetic simulations.
This role is ideal for candidates with strong domain knowledge in engineering or physical sciences and hands-on experience translating complex simulation data into robust, predictive machine learning models.
Required Qualifications
  • MS or PhD in Engineering (e.g., Chemical, Electrical, Mechanical, Aerospace, Nuclear, Materials), Science (e.g., Physics, Chemistry), or Computer Science
  • Significant experience developing machine learning or deep learning models using data from multi-dimensional numerical simulations (e.g., PDE-based solvers, particle-based simulations, multiphysics models)
  • Strong background in Python-based scientific computing and ML workflows
  • Demonstrated experience with PyTorch or equivalent deep learning frameworks
  • Solid understanding of:
    • Data preprocessing and feature engineering for large, high-dimensional datasets
    • Model training, validation, and performance evaluation
    • Numerical methods and/or physics-based modeling concepts

Preferred Qualifications
  • Experience with NVIDIA Physics NeMo, NVIDIA Modulus, or related physics-informed or simulation-driven ML libraries
  • Familiarity with GPU-accelerated computing, CUDA-aware workflows, and HPC environments
  • Exposure to physics-informed machine learning (PIML), surrogate modeling, reduced-order modeling, or operator learning
  • Publications or demonstrated research contributions in ML for physical systems or related fields

Key Responsibilities
  • Develop and train machine learning and deep learning models using data from large-scale, multi-dimensional HPC simulations
  • Collaborate with domain experts to incorporate physical constraints, scientific insight, and prior knowledge into ML model design
  • Design workflows for data ingestion, curation, and analysis of high-volume simulation outputs
  • Evaluate model accuracy, generalization, and robustness across a wide range of operating conditions
  • Optimize models for performance, scalability, and deployment on GPU-accelerated platforms
  • Contribute to internal software tools, modeling frameworks, and best practices

Additional Information
Time Type:
Full time
Employee Type:
New College Grad
Travel:
Yes, 10% of the Time
Relocation Eligible:
Yes
The salary offered to a selected candidate will be based on multiple factors including location, hire grade, job-related knowledge, skills, experience, and with consideration of internal equity of our current team members. In addition to a comprehensive benefits package, candidates may be eligible for other forms of compensation such as participation in a bonus and a stock award program, as applicable.
For all sales roles, the posted salary range is the Target Total Cash (TTC) range for the role, which is the sum of base salary and target bonus amount at 100% goal achievement.
Applied Materials is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.
In addition, Applied endeavors to make our careers site accessible to all users. If you would like to contact us regarding accessibility of our website or need assistance completing the application process, please contact us via e-mail at Accommodations_Program@amat.com, or by calling our HR Direct Help Line at 877-612-7547, option 1, and following the prompts to speak to an HR Advisor. This contact is for accommodation requests only and cannot be used to inquire about the status of applications.

What Applied Materials employees say

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About Applied Materials

Sourced by ZipRecruiter

Applied Materials is the global leader in materials engineering solutions used to produce virtually every new chip and advanced display in the world. We're the brain (and the brawn) behind every new technology development--whether it's building semiconductor chips for smartphones and computers, or the underpinnings for robotics, AI and even smart TV display screens. With 27,000 employees in 19 countries, we offer an exciting place to grow and learn alongside some of the best people you'll ever meet. We take deep pride in our Culture of Inclusion, and we celebrate the diverse backgrounds, perspectives and experiences that help us build stronger, more resilient teams. Join us as we innovate to Make Possible a Better Future!

Industry

Manufacturing

Company size

10,000+ Employees

Headquarters location

Santa Clara, CA, US

Year founded

1967

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