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Nvidia Machine Learning Jobs in California (NOW HIRING)

Nvidia

Senior AI Compiler Engineer

Santa Clara, CA · On-site

$122K - $168K/yr

We are seeking a Machine Learning Compiler Engineer with deep expertise in compiler technologies to ... NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering a diverse work ...

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Nvidia Machine Learning information

How much do NVIDIA machine learning engineers make?

NVIDIA machine learning engineers typically earn between $100,000 and $160,000 annually, depending on experience, location, and skill level. Senior roles or those with specialized expertise in deep learning and GPU programming can earn higher salaries, often exceeding $180,000. Compensation may also include bonuses and stock options in competitive tech environments.

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.

Does NVIDIA do machine learning?

Nvidia offers extensive tools and platforms for machine learning, including GPUs optimized for training and deploying models. Many machine learning engineers and researchers use Nvidia hardware and software frameworks like CUDA and cuDNN to accelerate AI development. The company also provides AI-focused products and solutions for various industries.

Is it hard to get hired at NVIDIA?

Getting hired for a machine learning role at NVIDIA can be competitive due to the company's focus on advanced technology and innovation. Candidates typically need strong technical skills in deep learning, programming, and relevant experience, along with a solid educational background. The hiring process often involves multiple interviews and technical assessments to evaluate expertise and problem-solving abilities.

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.

Is ML a high paying job?

Machine Learning roles, including positions like Nvidia Machine Learning engineers, are generally well-paid due to high demand for specialized skills in AI, data analysis, and programming. Salaries vary based on experience, location, and company, but these jobs tend to offer above-average compensation compared to many other tech roles.
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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 2% As Needed, 51% Full Time, 45% Part Time, and 2% Temporary. Highlights an 88% Physical, 6% Hybrid, and 6% Remote job distribution.
Senior Machine Learning and Simulation Engineer - Autonomous Vehicles

Senior Machine Learning and Simulation Engineer - Autonomous Vehicles

NVIDIA

Santa Clara, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

Job description

Job Summary:
NVIDIA is seeking exceptional Senior Machine Learning and Simulation Engineers to join their Autonomous Vehicles Simulation team. This role focuses on developing a Closed-Loop Simulation-based Reinforcement Learning framework to train advanced AV models and requires strong technical leadership and collaboration with various teams.
Responsibilities:
• Lead the design and development of large-scale RL training frameworks to accelerate the development of multi-modal AV foundation models.
• Design, build, and optimize simulation and data processing pipelines to enable scalable training of driving policies.
• Focus on measuring and enhancing simulation quality and refining the reward function for RL training.
• Ensure the reliability and performance of training workflows on large GPU clusters through the development of robust monitoring and debugging tools.
• Partner with researchers to integrate state-of-the-art model architectures into efficient and scalable training pipelines.
Qualifications:
Required:
• Bachelor's degree in Computer Science, Robotics, Engineering, or a related field (or equivalent experience).
• 12+ years of relevant professional experience encompassing large-scale ML training, AV systems, simulation, and AI infrastructure development.
• Deep proficiency in RL algorithms, such as PPO and GRPO, including practical experience with hyperparameter tuning and reward function design.
• Exceptional programming skills in C++ and Python, vital for developing efficient systems and data pipelines.
• Extensive experience with large-scale GPU clusters, High-Performance Computing (HPC) environments, and job scheduling/orchestration tools (e.g., Kubernetes, SLURM).
Preferred:
• Experience in RL infrastructure or general LLM training/fine-tuning infrastructure in industry.
• Experience in simulation & closed-loop evaluation of autonomous driving end-to-end models.
• Proven record on large-scale data pipeline development and algorithm optimization.
Company:
NVIDIA is a computing platform company operating at the intersection of graphics, HPC, and AI. Founded in 1993, the company is headquartered in Santa Clara, USA, with a team of 10001+ employees. The company is currently Late Stage.
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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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