Simulation Engineer

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.

We are seeking talented simulation engineers to create expansive simulated worlds to scale up robotic experience. You will have a dual focus: designing high-level virtual environments and enhancing low-level simulator software. This role requires a blend of technical expertise and collaborative skills, as you will work closely with our machine learning engineers and researchers. We are looking for candidates with diverse backgrounds, including game development, CGI artistry, animation, and interior design, who are passionate about turning their virtual creations into impactful real-world applications.

Responsibilities

• Design visually and physically realistic diverse scenes.
• Create new, specialized simulators optimized for high throughput, high fidelity data.
• Work with our ML and research team to deploy and/or improve simulators.

Preferred Qualifications

• BS, MS or higher degree in Computer Science, Robotics, Engineering or a related field, or equivalent practical experience.
• Proficiency in programming languages such as Python, C++, or similar.
• Deep understanding of commonly used physics engine simulators for robotics.
• Technical understanding of different components of a simulation - graphics, physics, etc.
• Experience in game development, CGI, or animation.
• Knowledge of robot design, controls, and robot hardware.
• Experience in inverse rendering or photogrammetry.