ZipRecruiter

Log In

1

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

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

$150K - $200K/yr

... physics. * Experience with Screamer, MAGIC, HYDRA, or similar circuit and plasma codes. * Proficiency in MHD and PIC simulation techniques. * Strong programming skills in Python, Fortran, C++, or ...

previous page

Showing results 41-60

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 Aug 21, 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 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.

What are the key skills and qualifications needed to thrive as a physics simulation Python developer?

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.

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.

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 August 2026, with employment types broken down into 1% Internship, 86% Full Time, 7% Part Time, and 6% Contract. Highlights an 79% Physical, 6% Hybrid, and 15% Remote job distribution, with an average salary of $82,773 per year, or $39.8 per hour.

Robot Learning Engineer -- Planning & Manipulation

Anyware Robotics

Fremont, CA • On-site

Full-time

Re-posted 13 days ago

Job description

Job Summary:
Anyware Robotics builds general-purpose mobile manipulator robots for industrial applications. We are looking for a Robot Learning Engineer to advance the planning and manipulation capabilities within AnywareOS, focusing on improving robot manipulation policies and collaborating with engineers to enhance operational performance.
Responsibilities:
• Improve learned policies for robot manipulation that augment and extend our production system's performance envelope
• Contribute to our manipulation capabilities: data collection from deployed robots, physics simulation environments, policy training, and deployment validation
• Use production multimodal data — rich sensor streams from real industrial operations across logistics and manufacturing
• Collaborate with perception and controls engineers to close the loop between scene understanding, navigation, and other capabilities inside AnywareOS
• Ship models to production — your work will run on robots at customer sites across multiple industries, not just on a sim bench
Qualifications:
Required:
• MS/PhD in ML, robotics, or related field (or equivalent industry experience shipping learned robotic behaviors)
• Strong applied ML fundamentals: policy learning (imitation learning, RL, or diffusion policies), neural network architecture design, training infrastructure
• Experience with robot learning for manipulation or motion: grasp synthesis, motion generation, trajectory optimization with learned components, or sim-to-real transfer
• Proficiency in Python and ML frameworks; comfortable with C++ for deployment-critical paths
• Understanding of classical planning (rule-based or optimization-based planning, task-space control)
• Demonstrated ability to go from research idea → working system
Preferred:
• Prior work on force/compliance control or contact-rich manipulation
• Familiarity with ROS2 and real robot deployment pipelines
• Experience with sim-to-real transfer at scale (domain randomization, system identification)
• Background in warehouse/logistics robotics or unstructured environment manipulation
• Publications at RSS, CoRL, ICRA, or NeurIPS robotics workshops
Company:
Anyware Robotics builds general-purpose robots for physically demanding work. Founded in 2023, the company is headquartered in Fremont, USA, with a team of 11-50 employees. The company is currently Early Stage.

Apply