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Physics Simulation Python Jobs in Berkeley, CA (NOW HIRING)

Skild AI

Machine Learning Engineer

San Mateo, CA · On-site

Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch ... Experience with physics simulation engines and tools for training RL. * Deep understanding of ...

UniversalAGI

AI Product Engineer

San Francisco, CA · On-site

Deep technical comfort with Python on the backend, alongside React, TypeScript, and Next.js on the ... Prior experience or background with 3D applications, CAD, physics simulations, or engineering ...

PhysicsX

Machine Learning Engineer

San Francisco, CA · On-site

By enabling high-fidelity, multi-physics simulation through AI inference across the entire ... Building machine learning models and pipelines in Python, using common libraries and frameworks (e ...

Fuse

Computational Physicist

San Leandro, CA · On-site

... physics, mathematics, and computational methods to develop models and simulations that explore ... Strong programming skills in Python, Fortran, C++, or MATLAB for numerical modeling. * Experience ...

PhysicsX

Data Scientist

San Francisco, CA · On-site

By enabling high-fidelity, multi-physics simulation through AI inference across the entire ... Expertise in python, along with proficiency in libraries like NumPy, SciPy, Pandas, TensorFlow and ...

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All JobsPhysics Simulation Python JobsPhysics Simulation Python Jobs in Berkeley, CA

Physics Simulation Python information

See Berkeley, CA salary details

$13.5K

$82.8K

$148.8K

How much do physics simulation python jobs pay per year?

As of Jul 10, 2026, the average yearly pay for physics simulation python in Berkeley, CA is $82,773.00, according to ZipRecruiter salary data. Most workers in this role earn between $53,900.00 and $97,300.00 per year, depending on experience, location, and employer.

What is the difference between Physics Simulation Python vs Mechanical Engineer?

AspectPhysics Simulation PythonMechanical Engineer
Required CredentialsProgramming skills, knowledge of physics, often a degree in physics or computer scienceMechanical engineering degree, professional licensure in some regions
Work EnvironmentSoftware development, research labs, simulation environmentsDesign offices, manufacturing plants, R&D departments
Industry UsageSimulation software development, research, academiaProduct design, manufacturing, systems optimization

Physics Simulation Python focuses on developing and implementing physics-based simulations using Python programming, often in research or software development contexts. Mechanical Engineers apply engineering principles to design, analyze, and manufacture mechanical systems. While both roles require a strong understanding of physics, Physics Simulation Python emphasizes coding and simulation, whereas Mechanical Engineering involves practical design and application in physical systems.

Does NASA hire physicists?

Yes, NASA hires physicists for roles involving research, space science, and engineering projects. These positions often require advanced degrees in physics or related fields and familiarity with scientific tools and data analysis methods. Physicists at NASA contribute to mission development, data interpretation, and technological innovation.

What are the key skills and qualifications needed to thrive as a Physics Simulation Python Developer, and why are they important?

To excel as a Physics Simulation Python Developer, you need a strong background in physics, mathematics, and proficiency in Python programming, often supported by a degree in physics, engineering, or computer science. Familiarity with simulation libraries (such as NumPy, SciPy, PyBullet, or SimPy), version control systems like Git, and experience with visualization tools are commonly required. Analytical thinking, problem-solving abilities, and effective collaboration are standout soft skills in this role. These skills enable the development of accurate, efficient simulations and foster productive teamwork in research or engineering projects.

What are some common challenges faced by professionals working in Physics Simulation with Python, and how can they be addressed?

Professionals in Physics Simulation with Python often encounter challenges such as optimizing simulation performance, ensuring numerical accuracy, and integrating complex libraries (e.g., NumPy, SciPy, PyBullet) into larger workflows. Addressing these issues typically involves using efficient coding practices, leveraging vectorized operations, and validating results with analytical solutions or experimental data. Collaboration with domain experts and regular code reviews can also help maintain code reliability and project scalability. Staying updated with the latest simulation frameworks and actively participating in open-source communities are excellent ways to overcome technical hurdles.

Is Python still in demand in 2026?

Python remains highly in demand for physics simulation roles in 2026 due to its versatility, extensive libraries like NumPy and SciPy, and strong community support. Professionals skilled in Python, along with knowledge of scientific computing and simulation frameworks, are sought after in research, engineering, and development environments.

Who hires computational physicists?

Computational physicists are hired by research institutions, government laboratories, universities, and private industry companies involved in scientific research, technology development, and simulation modeling. They often work in fields such as aerospace, defense, energy, and software development, utilizing programming skills and scientific expertise to solve complex physical problems.

What is a Physics Simulation Python developer?

A Physics Simulation Python developer is a professional who uses the Python programming language to design, implement, and analyze simulations that model physical systems and phenomena. These simulations can range from simple particle motion to complex fluid dynamics or electromagnetic fields, and are widely used in research, engineering, gaming, and education. The developer typically utilizes scientific libraries such as NumPy, SciPy, and PyBullet, and may also work with visualization tools to present simulation results. Their work helps in understanding real-world physics problems, testing hypotheses, or creating realistic interactive environments.

Is Python good for physics simulation?

Physics simulation Python roles often require knowledge of Python libraries such as NumPy, SciPy, and PyBullet, which are well-suited for modeling physical systems. Python's ease of use, extensive scientific computing ecosystem, and ability to integrate with other tools make it a popular choice for developing and running physics simulations in research and industry. Proficiency in numerical methods and understanding of physics principles are also important for these positions.
What are popular job titles related to Physics Simulation Python jobs in Berkeley, CA? For Physics Simulation Python jobs in Berkeley, CA, the most frequently searched job titles are:
What job categories do people searching Physics Simulation Python jobs in Berkeley, CA look for? The top searched job categories for Physics Simulation Python jobs in Berkeley, CA are:
What cities near Berkeley, CA are hiring for Physics Simulation Python jobs? Cities near Berkeley, CA with the most Physics Simulation Python job openings:
Physics Simulation Python jobs near you
Infographic showing various Physics Simulation Python job openings in Berkeley, CA as of July 2026, with employment types broken down into 100% Full Time. Highlights an 100% In-person job distribution, with an average salary of $82,773 per year, or $39.8 per hour.

Machine Learning Engineer, Reinforcement Learning

Skild AI

San Mateo, CA

Other

Re-posted 22 hours ago

Job description

Position Overview

We are looking for a Machine Learning Engineer to be responsible for designing and implementing cutting-edge reinforcement learning algorithms, conducting experiments, and optimizing these models to perform efficiently in real-world robotic environments. This will require close collaboration with our robotics, research, and engineering team. Your work will directly impact the development of intelligent, adaptable robots capable of learning and performing complex tasks autonomously.

Responsibilities
  • Develop and implement state-of-the-art reinforcement learning algorithms for robotic applications.
  • Design and conduct experiments to train RL models and conduct real-world tests.
  • Collaborate closely with researchers to explore novel methods of scaling up reinforcement learning model training.
  • Communicate effectively with inference, application, and deployment engineers to integrate RL models into robotic systems and iterate on methods to enable robust deployment.
  • Analyze and interpret experimental results, iterating on model design to achieve desired performance.
  • Stay up-to-date with the latest research and advancements in reinforcement learning.
Preferred Qualifications
  • BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
  • Proficiency in Python, C++, or similar and at least one deep learning library such as PyTorch, TensorFlow, JAX, etc.
  • Deep understanding and practical experience with various reinforcement learning algorithms and techniques (model-free, model-based, multi-task, hierarchical, multi-agent, etc.).
  • Strong background in algorithms, data structures, and software engineering principles.
  • Experience with physics simulation engines and tools for training RL.
  • Deep understanding of state-of-the-art machine learning techniques and models.
  • Extensive industry experience with reinforcement learning and robotic systems.

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