Lead advancements in physics simulation for robotics at Skild AI, contributing to innovative projects in a dynamic startup environment.
Posted by employer 9 months ago
First seen on Joblaze 1 week ago
Last verified on the company career page 1 day ago
Skills & Technologies
Requirements
- Education
- Master's degree
Not disclosed in this posting: years of experience, work arrangement, visa sponsorship.
Joblaze summary
The Physics Simulation Scientist at Skild AI focuses on enhancing the simulation and physics-solving framework essential for training robotic intelligence. This role requires expertise in GPU-accelerated physics engines and a strong background in physics simulation, particularly with high-dimensional robotics tasks. Ideal candidates are experienced professionals with a solid grasp of dynamics and optimization techniques, capable of collaborating with engineers and researchers to bridge the gap between simulation and real-world applications. Skild AI fosters a diverse team environment, welcoming individuals from various backgrounds to contribute to groundbreaking projects.
Joblaze insights
- Listed 9 days ago on Joblaze — tracked directly from Skild AI's career page.
- Skild AI has 63 other open roles including Manufacturing Engineering Manager, Senior Electrical Engineer , Operations Program Manager – Data Infrastructure - India.
- 6532 active Python roles on Joblaze right now.
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- Salary band is below the typical range for AI/ML roles (median ~$188,000).
- Pays more than 9% of the 3234 salaried Python roles we track (median $160,000). See Python salary trends
Quick facts
- What's the salary range?
- Skild AI lists $100,000–$300,000 for this role.
- What's the tech stack?
- Joblaze extracted these technologies from the posting: C++, CUDA, GPU, Machine Learning, Python, Robotics.
- What seniority level is this role?
- Skild AI targets senior candidates for this position.
- Is this full-time or contract?
- Full-time for this Physics Simulation Scientist role at Skild AI.
From the original posting
Company Overview
At Skild AI, we are building the world's first general purpose robotic intelligence that is robust and adapts to unseen scenarios without failing. We believe massive scale through data-driven machine learning is the key to unlocking these capabilities for the widespread deployment of robots within society. Our team consists of individuals with varying levels of experience and backgrounds, from new graduates to domain experts. Relevant industry experience is important, but ultimately less so than your demonstrated abilities and attitude. We are looking for passionate individuals who are eager to explore uncharted waters and contribute to our innovative projects.
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.