About the Team Join the Graphics Engine Team , where we push the boundaries of digital interaction by developing proprietary physics simulation, animation, and rendering systems. Our team merges pioneering research with robust engineering to build sophisticated frameworks and mathematical models that power dynamic simulations, advanced animation, and rendering solutions, while prioritizing real-time performance. We leverage modern machine learning technologies, to emulate complex physics interactions at speeds multiple orders of magnitude faster than traditional methods, and to tackle challenging computer graphics problems that no conventional technique can solve. We are committed to pioneering new frontiers in technology, ensuring remains at the forefront of innovation in the industry. Responsibilities - Optimize algorithms and systems for speed and scalability across a wide range of hardware and platform targets. - Work closely with product or other engineering teams to identify key challenges and deliver seamless, high-impact graphics solutions. - Stay up to date with the latest research in computer graphics, physics simulation, and machine learning. Contribute to internal knowledge-sharing and may publish findings in leading conferences or journals.
Minimum Qualifications: - MS or PhD in Computer Science, Applied Mathematics, or a related field, with a focus in computer graphics, physics simulation, animation or AI/ML - Combined Expertise: A solid background in both 3D computer graphics and AI is preferred - Mathematical Foundations: Strong background in linear algebra, calculus, geometry, and numerical methods. - Programming Skills: Proficiency in C++ and Python. Familiarity with GPU programming (CUDA, OpenCL, or similar) is a plus, but not required. - Machine Learning: Experience with deep learning frameworks (e.g., PyTorch, TensorFlow) and applying neural networks to graphics, simulation, or generative models is a strong plus. Preferred Qualifications - Relevant publications in top-tier computer graphics, vision, or ML conferences/journals (e.g., SIGGRAPH, ICCV, CVPR, NeurIPS). - Contributions to open-source projects, especially in graphics or simulation libraries.
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