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Physics Simulation Jobs in California (NOW HIRING)

Customize foundation models for Physics AI and physics simulation domain expertise through fine-tuning, prompt engineering, and evaluation frameworks * Deploy and scale LLM infrastructure : Build ...

Develop Flight Simulation Physics Models for eVTOL aircraft * Support vehicle level trade studies * Update system electrical, thermal, and performance model fidelity based on lab and flight test data ...

Physics Team Lead

San Francisco, CA ยท On-site

$210K - $250K/yr

We simulate how real-world catastrophes affect individual properties, translate that into ... As a Physics Team Lead on the Applied Science team, you will lead the development of core physics ...

Hands-on experience with modern robotics/physics simulation environments (e.g., Gazebo/Ignition, Isaac Sim/Omniverse, Unity, Unreal, MuJoCo, Webots ). A Final Note: If this role excites you, we ...

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Physics Simulation information

See California salary details

$10.9K

$66.7K

$119.9K

How much do physics simulation jobs pay per year?

As of Jun 12, 2026, the average yearly pay for physics simulation in California is $66,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $43,400.00 and $78,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Physics Simulation position, and why are they important?

To thrive in a Physics Simulation role, you need a solid background in physics, mathematics, and computer science, often supported by a relevant STEM degree. Proficiency in simulation software (such as MATLAB, ANSYS, or COMSOL), programming languages (like Python or C++), and familiarity with numerical modeling systems are typically required. Strong problem-solving skills, attention to detail, and effective collaboration and communication abilities are highly valued in this field. These competencies ensure accurate simulation results, efficient teamwork, and the ability to tackle complex real-world challenges in research or industry settings.

What are the typical daily tasks and responsibilities for someone working in Physics Simulation?

Professionals in Physics Simulation spend much of their day developing, testing, and refining computational models to represent physical phenomena, often collaborating with engineers and scientists to define simulation objectives. Responsibilities may include writing or optimizing code, analyzing simulation outputs, adjusting parameters to improve accuracy, and documenting methodologies and results. You might also participate in team meetings to review project milestones, discuss findings, and recommend design or process improvements based on your simulations. The role often involves both independent technical work and cross-disciplinary cooperation, making adaptability and clear communication important for success.

What is a Physics Simulation job?

A Physics Simulation job involves developing and implementing mathematical models to replicate real-world physical behaviors in software. Professionals in this field work with physics engines, numerical methods, and programming to simulate motion, collisions, fluid dynamics, or other physical phenomena. These simulations are used in industries such as gaming, film VFX, engineering, and scientific research to test and visualize complex systems. Strong skills in physics, programming (e.g., C++, Python), and computational techniques are essential for success in this role.

What are the most commonly searched types of Physics Simulation jobs in California? The most popular types of Physics Simulation jobs in California are:
What cities in California are hiring for Physics Simulation jobs? Cities in California with the most Physics Simulation job openings:

Systems Engineer - Simulation Correctness (Senior)

Vinci AI

Palo Alto, CA โ€ข On-site

$190K - $250K/yr

Full-time

Posted yesterday


Job description

The Mission
At Vinci, we are building the operator intelligence infrastructure that modern hardware programs rely on daily. We have already proven that a single foundation model works out of the box across physics on realistic production workloads.
  • Trained on PetaBytes of structured physics data
  • Running billion-voxel inference in production
  • Tier-1 semiconductor and hardware customers
  • Operating across multiple physical scales and operator regimes

We are scaling deployment at industrial magnitude:
  • Increase simulation throughput by two orders of magnitude
  • Expand simulation capabilities to maximize utility and domain coverage
  • Support global, multi-entity deployment across Tier-1 ecosystems

Our ambition is to become the default operator intelligence layer that hardware companies run on.
Design the Software that Designs Hardware
Integrating Machine Learning with Classic Numerical approaches results in a solution that is better than the sum of its parts. This method reduces the complexity of physics simulations, making them easier to setup, run and evaluate quickly. This combination of ease of use, speed and accuracy is the core of our value proposition to customers.
What You Will Do
Your north star will be the guaranteed (empirical) validation of simulation systems.
In this role you will use and evaluate the cutting edge solutions developed by our Machine Learning and Solver teams. Ensure that our customers receive the highest value results by building a runtime evaluation mechanism. Develop a compelling data driven argument for this mechanism. Work with software engineers to implement your designs and demonstrate validity.
You will sit at the interface of teams of Physicists, AI researchers, Software Engineers and Computational Geometry experts. You are comfortable working with deep technical experts and bringing your own expertise to bear.
What We're Looking For
Qualifications;
  • Prior experience using or building physics simulators
    • FEM, FEA, Molecular Dynamics, FDTD
  • Experience as a systems engineer in a production environment
    • working with Scientists and Engineers in a collaborative setting
  • Basic understanding of solver mechanisms;
    • Numerical Optimization, Convergence Criteria, Dampening approaches
  • Working knowledge of ML basics
    • back prop, loss functions, generators, embeddings, transformer models
  • Understanding of statistics and data science methods
    • Confidence intervals, uncertainty quantification, Bayes method

We are very excited to talk with you if you have
  • Worked as a Systems Engineer for a production Software Solution in any of;
    • Robotics, Chip Manufacturing, Aerospace
  • Have leveraged simulation for design or data generation purposes.
  • Have experience delivering solutions when needed
  • Have worked on validation solutions for a production ML system

Engineering Expectations
  • Software engineering fundamentals
    • Understanding of CI, regression testing, and validation discipline
  • Excellent communication and documentation skills
  • Comfortable running thousands of simulations and finding a needle in the haystack failure.
  • Capable of defining an architecture with sufficient detail an Engineer could implement it with few open questions.

Why Vinci
Join a rare early-stage startup that has successfully moved a foundational product from research to real-world, production environments, already serving Tier-1 semiconductor and hardware customers.
Our Mission & Impact
Vinci is building the operator intelligence infrastructure that modern hardware programs rely on daily. We are scaling our solution to accelerate design validation from hours to seconds. You will contribute to expanding our unified model architecture, which currently runs billion-voxel inference, into the transient domain-a key frontier in modeling interactions, deformation, and dynamics. Our ambition is to become the default operator intelligence layer for hardware companies.
Growth & Opportunity
This is a unique opportunity to be the first Systems Engineer in a burgeoning space and to build a practice and team around you. You will work with a premiere physics simulation tool-a proven foundation model capable of billion-voxel inference-that is scaling deployment across Tier-1 ecosystems. Our ambition is for this technology to become the default operator intelligence layer for hardware companies.
Leadership
You will work with spectacular technical leaders like CTO Sarah Osentoski and CEO Hardik Kabaria, whose vision is to greatly accelerate physics simulations with ML while retaining solver grade accuracy.