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

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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.
Senior/Staff Machine Learning Engineer

Senior/Staff Machine Learning Engineer

Dexterity

Redwood City, CA

$127K - $175K/yr

Other

Re-posted 8 days ago

Job description

About Dexterity
At Dexterity, we believe robots can positively transform the world. Our breakthrough technology frees people to do the creative, inspiring, problem-solving jobs that humans do best by enabling robots to handle repetitive and physically difficult work.

We're starting with warehouse automation, where the need for smarter, more resilient supply chains impacts millions of lives and businesses worldwide. Dexterity's full-stack robotics systems pick, move, pack, and collaborate with human-like skill, awareness, and learning capabilities. Our systems are software-driven and hardware-agnostic and have already picked 100+ million goods in production. And did we mention we're customer-obsessed? Every decision, large and small, is driven by one question - how can we empower our customers with robots to do more than they thought was possible?

Dexterity is one of the fastest-growing companies in robotics, backed by world-class investors such as Kleiner Perkins, Lightspeed Venture Partners, and Obvious Ventures. We're a diverse and multidisciplinary team with a culture built on passion, trust, and dedication. Come join Dexterity and help make intelligent robots a reality!

About the Role
As a Senior/Staff Machine Learning Engineer, you will be working on a myriad of challenges related to robot task and action planning. You will leverage techniques from machine learning to solve hard sequential decision problems that require reasoning about the physical world and its dynamics. You will also stay abreast of the latest progress in imitation learning, reinforcement learning, and other related fields in order to further develop Dexterity's technology foundations in Physical AI. Additionally, you will be responsible for updating and scaling our current ML pipelines to cover more scenarios and improve accuracy.

Dexterity's robotic solutions integrate data from a multitude of sensors, including RGB cameras, depth sensors, force-torque sensors, encoders, system telemetry and human input. To better inform the planning algorithms, you may work on sensor fusion and state estimation techniques to leverage this multimodal sensory data.

You will also work closely with the data platform, physics simulation, and robot operations teams to develop effective and efficient ways to improve the system's internal world model.

Dexterity has an expanding set of algorithmic challenges as we deploy new robotic applications, including areas such as:

- Improving packing algorithms to build taller, denser, more stable structures with a wider variety of objects.
- Solving the logistics task of moving and sorting inventory throughout a warehouse.
- Building models that understand physics and geometry for both short- and long-horizon tasks.

In addition to curating datasets and developing/improving machine learning models, you will be responsible for building data flywheels. Ideally, you will bring data-driven productization experience and help the team broadly in qualifying, deploying and updating models.
Responsibilities
  • Design and implement machine learning solutions across Dexterity's robotics stack, including but not limited to perception, decision-making, action scoring, and predictive modeling
  • Own the full ML development cycle for these solutions: data curation, labeling, training, evaluation, deployment, and iteration
  • Build performant training and inference pipelines using PyTorch, with production-readiness and scalability in mind
  • Collaborate closely with robotics, data platform, and simulation teams to integrate ML into real-time, latency-sensitive robotic systems
  • Use profiling, monitoring, and experiments to optimize model performance and reliability
  • Ensure reproducibility, traceability, and modularity across training and serving pipelines
  • Maintain clean, production-quality code in Python (and C++ where required)
  • Help establish best practices for model versioning, dataset management, and ML operations
Required Skills
  • Degree in Computer Science, Electrical Engineering, or Mathematics 5+ years of industry experience applying machine learning to real-world, production systemsStrong Python skills and deep experience with PyTorch
  • Ability to work fluently across ML tasks, e.g., classification, regression, ranking, segmentation, and structured prediction
  • Strong engineering background with experience profiling, debugging, and optimizing model and pipeline performance
  • Proven ability to design and maintain reliable systems, from model training to field deployment
  • Experience with cloud-based infrastructure (AWS, GCP, Azure) and containerized environments (Docker)
  • Familiarity with Linux, Git, CI/CD) and software development best practices (unit/acceptance/integration testing, code reviews)
Nice to haves
  • Prior experience in robotics, autonomous systems, or real-time ML applications
  • Exposure to multimodal data (e.g., RGBD, force-torque, pose estimates, telemetry)
  • Experience deploying models using serving stacks like NVIDIA Triton, TorchServe, or custom low-latency frameworks
  • Background in computer vision, geometric learning, or time-series modeling
  • Experience with Kubernetes, Ray or other distributed training and inference systems
  • Previous startup experience or experience in fast-paced, cross-disciplinary environments
$170,000 - $225,000 a year
Our Total Rewards philosophy is designed to recognize contributions toward meaningful innovation. Base pay is one component of a broader compensation package that may include equity grants, benefits, and other incentives, depending on role and eligibility.

For this position, the expected base salary range is $170,000 to $225,000 annually. Actual compensation will be determined based on skills, experience, education, and market factors, and may vary accordingly.

Final compensation decisions are made individually and take a number of factors into consideration. Eligible employees may be considered for equity awards as part of their overall compensation. Access to benefits and wellness resources is provided in accordance with company policies and may vary based on role and location.

Equal Opportunity Employer
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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