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About Hyper Hyper's goal is to build the world's best avatar tools. We're starting with VTubing as our first use-cas...

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Machine Learning Engineer Generative 3D Computer Vision AI Companions

Hyper Online

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$0k · Senior Full-time Posted over 2 years ago 2 min read

Hyper is seeking a dedicated Applied Machine Learning Engineer with an expertise in 3D graphics, animation, motion capture, and computer vision. As part of our team, you will implement and deploy cutting-edge models focused on enhancing avatar fidelity and overall user experience. If you love to quickly put into practice the latest research, constantly push the limits of technology, and create compelling digital experiences, this role is for you.

Your Role:

💻 Apply state-of-the-art machine learning models to improve the fidelity of our avatars, enhancing their 3D graphics, animation, and motion capture systems.

🎞️ Utilize computer vision techniques to improve user interaction with our platform, pushing the boundaries of immersive avatar experiences.

🧪 Convert latest research findings and papers into applied solutions that improve our product.

⚙️ Test, validate, and deploy machine learning solutions, working with large datasets, and iteratively improving our models and techniques.

Qualifications:

🔧 5+ years of experience in applying and deploying ML models, especially in the domains of computer vision, 3D asset generation, or 3D animation generation, or a robust portfolio of projects that demonstrate your expertise in machine learning applied to 3D graphics, animation, motion capture, and/or computer vision.

🎨 Proficiency in tools and languages used in 3D modeling, animation, and computer vision such as Python, OpenCV, Maya, Blender, or similar.

🧮 Strong knowledge of machine learning algorithms and principles, as well as experience with ML frameworks like TensorFlow, PyTorch, or Keras.

📈 Experience working with large datasets and ability to manipulate and improve them to enhance model performance.

📝 Excellent written communication skills, essential for effective collaboration in our remote working environment.

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