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Senior Simulation Engineer Jobs in Mountain View, CA

Senior Simulation Engineer Onsite

San Jose, CA · On-site

$122K - $168K/yr

Experience with campaign analysis simulation tools * Experience applying the physics of magnetism in a practical, research, engineering, or laboratory setting. Learn More and Apply Now! * ​Onsite:

Senior Level Salary: $180,000 - $250,000 per year We're looking for a Chip Simulation Engineer to build software environments that model and simulate advanced compute architectures before or without ...

New

We are looking for a Senior Simulation Software Engineer to build and scale the simulation infrastructure that powers our autonomous vehicle development. You will architect simulation pipelines ...

We are looking for a Senior Simulation Software Engineer to build and scale the simulation infrastructure that powers our autonomous vehicle development. You will architect simulation pipelines ...

We are looking for a Senior Simulation Software Engineer to build and scale the simulation infrastructure that powers our autonomous vehicle development. You will architect simulation pipelines ...

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Senior Simulation Engineer information

See Mountain View, CA salary details

$70.2K

$149.2K

$216.4K

How much do senior simulation engineer jobs pay per year?

As of Sep 4, 2026, the average yearly pay for senior simulation engineer in Mountain View, CA is $149,220.00, according to ZipRecruiter salary data. Most workers in this role earn between $123,200.00 and $169,200.00 per year, depending on experience, location, and employer.

What is a senior simulation engineer?

Senior Simulation Engineers are experienced professionals who design, develop, and analyze complex simulations to model real-world systems and processes. They use advanced software tools and mathematical models to predict performance, identify potential issues, and optimize designs in fields such as aerospace, automotive, manufacturing, and energy. Their work helps organizations make informed decisions and improve product reliability and efficiency. Senior Simulation Engineers often lead teams, mentor junior engineers, and collaborate with cross-functional groups to ensure the effective implementation of simulation solutions.

What are the typical collaboration points between a senior simulation engineer and other engineering teams?

As a Senior Simulation Engineer, you will frequently collaborate with cross-functional teams such as design, development, and testing to ensure simulation models accurately reflect real-world conditions. This often involves attending design reviews, sharing simulation results, and providing feedback to optimize product performance. Effective communication and teamwork are essential, as your insights directly influence design decisions and help troubleshoot issues early in the development cycle. Regular meetings and shared documentation platforms are commonly used to keep everyone aligned and informed.

What are the key skills and qualifications needed to thrive as a senior simulation engineer, and why are they important?

To thrive as a Senior Simulation Engineer, you need a strong background in engineering principles, mathematics, and physics, typically with a relevant bachelor's or master's degree. Proficiency in simulation software such as MATLAB, Simulink, ANSYS, or similar tools, along with experience in programming languages like Python or C++, is essential. Excellent problem-solving skills, attention to detail, and effective communication are crucial soft skills for collaborating with multidisciplinary teams and interpreting complex data. These competencies ensure accurate modeling, effective project delivery, and innovation in designing and optimizing engineering systems.

What is the difference between Senior Simulation Engineer vs Simulation Engineer?

AspectSenior Simulation EngineerSimulation Engineer
Required CredentialsBachelor's or Master's in Engineering, experience in simulation softwareBachelor's in Engineering or related field, basic simulation skills
Work EnvironmentDesign teams, R&D departments, engineering firmsDevelopment teams, testing labs, manufacturing companies
Employer & Industry UsageAutomotive, aerospace, electronics, manufacturingSimilar industries, often entry to mid-level roles

The main difference between a Senior Simulation Engineer and a Simulation Engineer lies in experience and responsibility. Senior roles typically require more advanced skills, leadership, and project oversight, whereas Simulation Engineers focus on executing simulation tasks under supervision. Both roles are vital in industries like automotive and aerospace, but senior positions involve strategic planning and mentorship.

What are the most commonly searched types of Simulation Engineer jobs in Mountain View, CA?

The most popular types of Simulation Engineer jobs in Mountain View, CA are:

What job categories do people searching Senior Simulation Engineer jobs in Mountain View, CA look for?

The top searched job categories for Senior Simulation Engineer jobs in Mountain View, CA are:

What cities near Mountain View, CA are hiring for Senior Simulation Engineer jobs?

Cities near Mountain View, CA with the most Senior Simulation Engineer job openings:

Infographic showing various Senior Simulation Engineer job openings in Mountain View, CA as of June 2026, with employment types broken down into 2% As Needed, 44% Full Time, 47% Part Time, 2% Temporary, and 5% Contract. Highlights an 88% Physical, 4% Hybrid, and 8% Remote job distribution, with an average salary of $148,188 per year, or $71.2 per hour.

Senior Simulation Engineer - W2 Role

Saransh Inc

Mountain View, CA • On-site

Contractor

Re-posted 26 days ago


Job description

Role: Senior Simulation Engineer
Location: Mountain View, CA (Hybrid Onsite)
Job Type: W2 Contract
 
Job Description: 
  • We are seeking a highly skilled Senior Simulation Engineer to own and accelerate our synthetic data generation capabilities.
  • This role is crucial for bridging the gap between our high-fidelity simulation environment and our production ML models.
  • You will be responsible for architecting, implementing, and maintaining the entire simulation-to-data pipeline, ensuring a consistent and massive flow of quality training data.
Key Responsibilities:
  • Simulation Acceleration & Data Collection: Directly utilize expertise in NVIDIA Isaac Sim to design, script, and optimize simulation scenarios specifically tailored to generate high-quality, diverse data for VLA (Vision-Language Alignment) and NOVA model training objectives.
  • Pipeline Architecture: Design, build, and maintain robust, scalable pipelines for CAD ingestion, scene creation, sensor emulation, and data processing within the Isaac Sim framework.
  • Synthetic Data Management: Implement and manage advanced auto-annotation tools within the simulation environment to rapidly label complex sensory data (e.g., 3D bounding boxes, semantic segmentation, depth maps) for supervised learning.
  • Environment Maintenance: Take ownership of setting up, configuring, and maintaining the simulation environment (including hardware/software dependencies, GPU utilization, and headless operation) to ensure reliable, large-scale parallel execution.
  • Cross-Functional Support: Collaborate closely with the Machine Learning Engineering team to analyze data gaps, iterate on simulation parameters, and ensure the synthetic data distribution matches the necessary complexity and variability of real-world deployment.
  • Performance Tuning: Profile and optimize simulation execution speed to maximize data throughput, essential for rapid iteration cycles in model tuning.
Required Qualifications:
  • Expertise in Simulation: 3+ years of hands-on experience with NVIDIA Isaac Sim (or a comparable high-fidelity physics simulator like Unity/Unreal used for robotics).
  • Programming Proficiency: Expert-level proficiency in Python for scripting, automation, data pipeline construction, and tool development.
  • Robotics Fundamentals: Strong understanding of robotics kinematics, sensor physics (LIDAR, RGB-D cameras, IMU), and their accurate representation in simulation.
  • ML Data Pipeline Experience: Proven experience setting up automated data collection pipelines for Deep Learning projects, including experience with data versioning and metadata management.
  • CAD/3D Workflow: Familiarity with 3D assets, CAD formats, and procedural generation techniques to create complex virtual scenes.
Preferred Qualifications:
  • Familiarity with VLA/NOVA model architectures or similar foundation models in robotics.
  • Experience with cloud computing environments (AWS, Azure, GCP) for scaling simulation jobs.
  • Familiarity with other robotics simulation/middleware like ROS/ROS 2.
  • Experience with hardware-in-the-loop (HIL) or software-in-the-loop (SITL) testing methodologies.