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Nvidia Simulation Jobs in California (NOW HIRING)

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Nvidia Simulation information

What jobs pay the most at NVIDIA?

At NVIDIA, executive roles such as Vice President and Senior Director tend to have the highest salaries, often complemented by bonuses and stock options. High-paying technical roles include AI researchers, software engineers, and hardware architects with advanced skills in machine learning, GPU architecture, and deep learning. These positions typically require advanced degrees and specialized expertise.

What is the difference between Nvidia Simulation vs Nvidia Software Engineer?

AspectNvidia SimulationNvidia Software Engineer
Required CredentialsBachelor's or higher in Computer Science, Engineering, or related fields; experience with simulation toolsBachelor's or higher in Computer Science, Software Engineering, or related fields; programming skills
Work EnvironmentResearch labs, simulation development teams, hardware-focused projectsSoftware development teams, product engineering, application development
Industry UsageAutonomous vehicles, robotics, physics modelingGraphics, AI, driver software, system optimization
Common Search/ComparisonYesYes

While Nvidia Simulation specialists focus on developing and testing simulation models for hardware and autonomous systems, Nvidia Software Engineers work on designing, coding, and maintaining software applications across various Nvidia products. Both roles require strong programming skills and collaboration within tech teams, but they differ in their core focus areas and project types.

How difficult is it to get hired at NVIDIA?

Getting hired at NVIDIA for simulation-related roles can be competitive, often requiring strong technical skills in areas like GPU programming, simulation software, and relevant experience. Candidates typically go through a rigorous interview process that assesses technical knowledge, problem-solving abilities, and cultural fit.

What is NVIDIA's starting salary?

The starting salary for NVIDIA simulation roles typically ranges from $70,000 to $100,000 annually, depending on experience, education, and location. Entry-level positions often include benefits such as health insurance and stock options, with additional compensation for skills in programming, GPU architecture, and simulation tools.
Infographic showing various Nvidia Simulation job openings in California as of June 2026, with employment types broken down into 1% As Needed, 86% Full Time, and 13% Part Time. Highlights an 83% Physical, 8% Hybrid, and 9% Remote job distribution.
Senior Solutions Architect, Robotics Infrastructure

Senior Solutions Architect, Robotics Infrastructure

NVIDIA

Santa Clara, CA • On-site

Full-time

Posted 17 days ago

Job description

Job Summary:
NVIDIA is a leading technology company focused on building innovative solutions for Physical AI. They are seeking a Senior Solutions Architect with expertise in backend infrastructure and cloud-native applications to design and scale Kubernetes-native environments for distributed AI/ML workloads, particularly in robotics simulation and inference.
Responsibilities:
• Support customers in building scalable and observable GPU-accelerated pipelines for key robotics workloads using Kubernetes, cloud-native technologies, and NVIDIA frameworks (OSMO, Dynamo) across heterogeneous infrastructure.
• Develop a deep understanding of robotics workloads scaling and help translate those into optimal architectures for partners.
• Collaborate with DevOps teams to orchestrate data preprocessing, distributed training and inference workloads to optimize job scheduling, costs, storage access, and networking across hybrid and multi-cloud Kubernetes environments (e.g., AWS, Azure, GCP, on-prem).
• Accelerate inference pipelines using NVIDIA NIM, TensorRT-LLM, vLLM, SGLang, and other engines to enable seamless, disaggregated inference architectures.
• Collaborate with multi-functional teams (business, engineering, product) and provide technical mentorship to customers implementing Physical AI at scale.
Qualifications:
Required:
• 5+ Years of experience in Solution Architecture or Infrastructure Engineering, advancing AI/ML systems from proof of concept to production on private/public cloud environments.
• Experience with scaling Robotics workloads in one or more areas, such as VLM/VLA model training, model inference, robot learning and simulation, data generation.
• Strong expertise in networking (DNS, LB, TCP/IP, firewalls), storage technology, workflow orchestration softwares (Airflow, Argo, etc), modern DevOps practices (GitOps, IaC, Observability), and orchestrating efficient GPU workloads using the NVIDIA GPU Operator and MIG.
• Excellent communication skills to convey technical concepts to diverse audiences.
• BS in Computer Science, Computer Engineering, or a related field, or equivalent experience.
Preferred:
• Proficiency with robotics frameworks (e.g., ROS2) and NVIDIA simulation and AI platforms such as Isaac Lab, Isaac Sim or Cosmos.
• Experience with AI/ML training workflows and distributed job orchestration using tools like Ray.
• Deep expertise of transformer networks and experience deploying NVIDIA inference technologies (Dynamo, NIM, Triton, vLLM) using acceleration techniques like quantization.
• Experience with large scale data curation techniques and optimization.
• Broad technical expertise across networking, compute, and storage systems (e.g., S3, NFS, Lustre), with hands-on experience building and debugging APIs (REST, gRPC) as well as relevant certifications such as NVIDIA Certified AI Engineer, Certified Kubernetes Administrator (CKA), or Cloud Solutions Architect.
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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