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Physics Simulation Python Jobs (NOW HIRING)

Agility Robotics

Senior Manager, Simulation

Salem, OR · On-site +1

$208K - $324K/yr

Proficiency in modern C++ and Python * Experience with at least one major robotics physics simulator (MuJoCo, IsaacSim, Gazebo, or similar) * Familiarity with standard software development practices:

Agility Robotics

Senior Manager, Simulation

Fremont, CA · On-site +1

$208K - $324K/yr

Proficiency in modern C++ and Python * Experience with at least one major robotics physics simulator (MuJoCo, IsaacSim, Gazebo, or similar) * Familiarity with standard software development practices:

Agility Robotics

Senior Manager, Simulation

Pittsburgh, PA · On-site +1

$208K - $324K/yr

Proficiency in modern C++ and Python * Experience with at least one major robotics physics simulator (MuJoCo, IsaacSim, Gazebo, or similar) * Familiarity with standard software development practices:

Agility Robotics

Senior Manager, Simulation

Salem, OR · On-site +1

$208K - $324K/yr

Proficiency in modern C++ and Python * Experience with at least one major robotics physics simulator (MuJoCo, IsaacSim, Gazebo, or similar) * Familiarity with standard software development practices:

NVIDIA Corporation

$184 - $357/hr

... and physics simulation technologies. What you'll be doing: Building simulation frameworks for ... Proficiency using Python and development experience with deep learning software stacks (Pytorch ...

New

1X

Software Engineer - Simulation

San Carlos, CA · On-site

Required : • 4+ years of experience programming in Python, C++, or similar languages, with ... of physics simulators or OpenGL rendering pipelines • Strong testing practices for simulation ...

Dyna Robotics, Inc

$150 - $230/hr

Rendering for ML, Not Just Physics: Push photorealistic rendering quality specifically to close the ... Strong Python skills; comfort with PyTorch or JAX for anything touching model training/eval.

Red Gate Group

Physicist

Albuquerque, NM · On-site

The ideal candidate brings a strong physics foundation, hands-on simulation experience, and the ... Proficiency in scripting or programming languages (Python, MATLAB, or Fortran) for pre/post ...

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Physics Simulation Python information

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How much do physics simulation python jobs pay per year?

As of Aug 22, 2026, the average yearly pay for physics simulation python in the United States is $67,601.00, according to ZipRecruiter salary data. Most workers in this role earn between $44,000.00 and $79,500.00 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.

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Physics Simulation Python jobs near you
Infographic showing various Physics Simulation Python job openings in the United States as of August 2026, with employment types broken down into 1% Internship, 87% Full Time, 6% Part Time, and 6% Contract. Highlights an 76% Physical, 7% Hybrid, and 17% Remote job distribution, with an average salary of $67,601 per year, or $32.5 per hour.

Research Engineer/Scientist, Simulation

DYNA Robotics Inc

Redwood City, CA • On-site

Full-time

Posted 17 days ago

Job description

Dyna Robotics makes general-purpose robots powered by a proprietary embodied AI foundation model that generalizes and self-improves across varied environments with commercial-grade performance. Dyna's robots have been deployed at customers across multiple industries. Its frontier model has the top generalization and performance in the industry.
Dyna Robotics has raised over $140M, backed by top investors including CRV, First Round Capital, Robostrategy, Salesforce Ventures, NVentures, Amazon, Samsung Next, and LG Technology Ventures. Our team brings together engineers and researchers from Google, Meta, Apple, Amazon, Cruise, Aurora, NVIDIA, along with academic roots at Stanford, Berkeley, MIT, UPenn, and beyond. We're positioned to redefine the landscape of robotic automation.
POSITION OVERVIEW
As a Research Engineer/Scientist focused on Simulation, you will build the simulated worlds that power Dyna's loco-manipulation policies. Our robot is a wheeled mobile manipulator. Mobility and manipulation are tightly coupled, not two separate problems, so simulating one without the other misses what actually matters for our policies. You'll own the pipeline end-to-end: from real-to-sim reconstruction of the facility-scale environments our robots navigate, through procedural scene generation, to sim-based training data and evaluation for policies that jointly control base motion and arm manipulation.
WHAT YOU'LL DO
Real-to-Sim Reconstruction: Build a pipeline that reconstructs real, facility-scale environments into simulation (3D reconstruction, photorealistic re-rendering). That means full rooms and aisles our wheeled base navigates, not just tabletop scenes.
Facility-Scale Scene Generation: Procedurally generate navigable environments (layouts, obstacles, object placement) that stress-test loco-manipulation policies across the range of spaces our robots actually operate in.
Loco-Manipulation Sim-for-Data-Gen: Generate synthetic training data for policies that jointly reason about base positioning and arm manipulation (approach angles, reachability, obstacle-aware repositioning), and feed real-world failure modes back into new sim scenarios.
Loco-Manipulation Evaluation: Build simulation benchmarks that test the joint base+arm policy (VLA / imitation learning / diffusion models) as a whole, not manipulation in isolation on a fixed base.
Rendering for ML, Not Just Physics: Push photorealistic rendering quality specifically to close the sim-to-real gap for vision-based loco-manipulation. Rendering fidelity is a first-class deliverable, not an afterthought on top of physics accuracy.
Cross-Team Collaboration: Partner with the AI Research team on where simulated data and evaluation most accelerate loco-manipulation policy development, and with Data Ops on what's worth capturing in the real world vs. generating in sim.
WHAT YOU'LL BRING
  • MS or PhD in CS/Robotics/Graphics, or equivalent hands-on experience. We care more about demonstrated depth building simulation/rendering systems than a fixed years-of-experience bar.
  • Hands-on experience with simulation stacks (MuJoCo, Isaac Sim/Isaac Lab, SAPIEN, Omniverse, Blender, or similar) for robotics or graphics.
  • Experience with procedural scene/asset generation, domain randomization, or photorealistic rendering pipelines at scale (not academic-scale one-off scenes).
  • Familiarity with training/evaluating manipulation or loco-manipulation policies (imitation learning, VLA, diffusion, or RL) and how simulated data actually feeds into them.
  • Experience simulating mobile bases (wheeled, tracked, or holonomic) is a real plus. Most of the field's simulation talent comes from fixed-arm tabletop manipulation or legged-humanoid balance/gait work, and neither maps cleanly onto a wheeled mobile manipulator.
  • Prior research or engineering background in loco-manipulation or whole-body control itself, coordinating mobile-base motion with arm manipulation, independent of any simulation-specific experience.
  • Strong Python skills; comfort with PyTorch or JAX for anything touching model training/eval.
  • Senior enough to define your own research agenda and exercise independent judgment on where simulation adds the most leverage. This is closer to a founding-type ownership role than a narrow IC slot on an existing pipeline.
BONUS POINTS FOR
  • Experience with real-to-sim-to-real pipelines (3D reconstruction, NeRF/Gaussian splatting, differentiable rendering).
  • Exposure to world-model / video-prediction research (e.g. learned dynamics or latent world models) as a complement to classical physics simulation.
  • GPU-scale physics simulation experience (CUDA, large-batch parallel sim) rather than single-instance sim.
  • Background simulating wheeled/mobile manipulators specifically (e.g. Boston Dynamics Stretch, warehouse/logistics robotics) rather than legged humanoids or fixed-base arms.
  • Publications at CoRL, RSS, ICRA, NeurIPS, CVPR, or SIGGRAPH.
  • Experience leading or mentoring within a small research team.

At Dyna Robotics, we build technology for the real world, which requires a team as diverse as the environments our robots inhabit. We are an equal opportunity employer committed to technical rigor and mutual respect.
Don't let a checklist stop you. Data shows that underrepresented groups often only apply if they meet 100% of the criteria. We value problem-solving and grit over keyword matching. If you're passionate about the intersection of geometry and robotics, we want to hear from you, even if you don't check every box.

Apply