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Skild AI

Physics Simulation Scientist

San Mateo, CA · On-site

Position Overview We are seeking a Physics Simulation Scientist to lead advancements in the simulation and physics-solving backbone behind Skild's robot foundation model training. You will ...

Mondelez International

Plan, lead, and manage modelling and simulation projects, scoping and proposing opportunities for sustained business impact. * Work closely with engineers and scientists to define complex technical ...

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As of Jul 15, 2026, the average yearly pay for simulation scientist in the United States is $81,521.00, according to ZipRecruiter salary data. Most workers in this role earn between $59,000.00 and $99,000.00 per year, depending on experience, location, and employer.
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Infographic showing various Simulation Scientist job openings in the United States as of July 2026, with employment types broken down into 1% As Needed, 91% Full Time, 5% Part Time, and 3% Contract. Highlights an 92% Physical, 2% Hybrid, and 6% Remote job distribution, with an average salary of $81,521 per year, or $39.2 per hour.

Physics Simulation Scientist

Skild AI

San Mateo, CA • On-site

Other

Posted 6 days ago

Job description

Position Overview

We are seeking a Physics Simulation Scientist to lead advancements in the simulation and physics-solving backbone behind Skild's robot foundation model training. You will collaborate with external experts in GPU-accelerated physics engines and work with our internal robotics and learning teams to build a next-generation, open-source simulation stack for robotics sim-to-real.

You'll partner closely with engineers scaling simulation scene generation and with ML researchers pushing the limits of sim-to-real transfer. The ideal candidate brings deep physics-simulation expertise plus hands-on experience implementing and optimizing algorithms on modern GPUs.

Responsibilities
  • Improve and develop new physics solvers and modeling methods for high-DoF, contact-rich robotics tasks.
  • Design and implement GPU-accelerated solvers with a focus on throughput, stability, and scalability.
  • Profile and optimize simulation performance on modern GPU hardware and distributed clusters.
  • Work with external collaborators and the open-source community to advance simulation for robotics.
  • Collaborate with scene-generation engineers to scale robotic experience across diverse real-world environments.
  • Partner with ML researchers to improve sim-to-real transfer through better physical modeling, calibration, and training regimes.
  • Contribute to the long-term technical direction of Skild's physical modeling and sim-to-real strategy.
Preferred Qualifications
  • MS or PhD in Physics, Robotics, Computer Science, Applied Math, Engineering, or a related field, or equivalent hands-on experience.
  • Strong track record working on physics engines or high-fidelity simulators for articulated rigid bodies; experience with deformables, fluids, or differentiable simulation is a plus.
  • Deep understanding of dynamics, contact modeling, constraint-based methods, and integrators, including accuracy-speed tradeoffs.
  • Expertise in CUDA and GPU programming with proven ability to optimize for scale.
  • Proficiency in C++ and Python, and experience building reliable systems used by other technical teams.
  • Familiarity with how modern ML/RL pipelines consume simulation (vectorized environments, domain randomization, large-scale rollouts).
  • Experience with real robot platforms and strong intuition for where simulation diverges from reality.
  • Publications, open-source contributions, or shipped systems in simulation, robotics, graphics, or numerical computing are a strong plus.

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