Deep Learning Scientist/ Applied Scientist (Neural Rendering/Vision)

You will be responsible for utilizing cutting-edge DL techniques to develop advanced algorithms for neural rendering using Python and popular deep learning frameworks. In this role, you will collaborate closely with a team of passionate researchers and developers to address complex challenges in deep learning, including multi-modal image synthesis, audio-visual data fusion, and image/video transformation. Your key responsibilities will include enhancing the performance of products to ensure high levels of accuracy, speed, and scalability, with guidance from senior team members. You will also integrate developed software, algorithms, and AI models into products and services, working collaboratively with stakeholders. Additionally, you will maintain the software's security, reliability, and maintainability following senior team members' guidance. Finally, you will conduct thorough testing and validation to meet the desired performance objectives. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 3+ years of industry or research experience in deep learning and computer vision, focusing on areas such as computational photography, neural talking head synthesis, representation and synthesis of lifelike facial attributes, video synthesis, etc. - Experience with self-supervised, few-shot, or zero-shot learning techniques for image synthesis, as well as domain adaptation techniques for face image synthesis. - Strong understanding of Generative networks (for use-cases like Super-resolution, Inpainting, etc.) and state-of-the-art deepfake algorithms. - Minimum 2 years of relevant experience with generative networks like Transformers, GANs, Auto-encoders, Diffusion models, etc. - Minimum 1 year of experience with Vision Transformers. - Experience with Multi-modal image synthesis with audio-visual data. - Proficiency in Python programming and deep learning frameworks like PyTorch or TensorFlow, with at least 3 years of experience. - Experience in developing scalable tools and solutions for real-world computer vision problems or visual effects. - Exceptional problem-solving skills and the ability to work effectively in a team environment. Bonus: - MS or Ph.D. in Visual Computing, Computer Vision, Machine Learning, or related field. - Experience with 3D GANs for human body/face synthesis. You will be responsible for utilizing cutting-edge DL techniques to develop advanced algorithms for neural rendering using Python and popular deep learning frameworks. In this role, you will collaborate closely with a team of passionate researchers and developers to address complex challenges in deep learning, including multi-modal image synthesis, audio-visual data fusion, and image/video transformation. Your key responsibilities will include enhancing the performance of products to ensure high levels of accuracy, speed, and scalability, with guidance from senior team members. You will also integrate developed software, algorithms, and AI models into products and services, working collaboratively with stakeholders. Additionally, you will maintain the software's security, reliability, and maintainability following senior team members' guidance. Finally, you will conduct thorough testing and validation to meet the desired performance objectives. Qualifications Required: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 3+ years of industry or research experience in deep learning and computer vision, focusing on areas such as computational photography, neural talking head synthesis, representation and synthesis of lifelike facial attributes, video synthesis, etc. - Experience with self-supervised, few-shot, or zero-shot learning techniques for image synthesis, as well as domain adaptation techniques for face image synthesis. - Strong understanding of Generative networks (for use-cases like Super-resolution, Inpainting, etc.) and state-of-the-art deepfake algorithms. - Minimum 2 years of relevant experience with generative networks like Transformers, GANs, Auto-encoders, Diffusion models, etc. - Minimum 1 year of experience with Vision Transformers. - Experience with Multi-modal image synthesis with audio-visual data. - Proficiency in Python programming and deep learning frameworks like PyTorch or TensorFlow, with at least 3 years of experience. - Experience in developing scalable tools and solutions for real-world computer vision problems or visual effects. - Exceptional problem-solving skills and the ability to work effectively in a team environment. Bonus: - MS or Ph.D. in Visual Computing, Computer Vision, Machine Learning, or related field. - Experience with 3D GANs for human body/face synthesis.