3 Neural Rendering Jobs

You are sought after to be a Research-Oriented Technical Artist who goes beyond using creative tools to scripting them, adapting them, and constructing new workflows from the ground up. Your focus will not be on production pipelines but on pushing visual boundaries in Mixed Reality by means of experimentation, custom rendering, and procedural creativity. If you have a passion for writing shaders, automating pipelines in Blender or Houdini, and envisioning groundbreaking visuals that are yet to be witnessed, then this position is tailored for you. Your responsibilities will include prototyping new visuals, effects, and rendering techniques for Mixed Reality, crafting custom shaders (GLSL, HLSL, OSL, Shader Graph, etc.), scripting and automating workflows in tools like Blender, Maya, Houdini, or similar software, applying a profound comprehension of 2D/3D rendering principles, lighting, materials, and post-effects, collaborating closely with developers and designers to actualize concepts across MR devices, and exploring the visual lexicon of Mixed Reality to introduce new aesthetics and interaction paradigms. To qualify for this role, you should possess 2 to 5+ years of experience as a Technical Artist, Shader Artist, or Visual R&D Specialist, a solid foundation in real-time and offline rendering basics, proficiency in scripting within Blender (Python), Maya (MEL/Python), Houdini (VEX/HScript), or similar tools, the ability to create and troubleshoot custom shaders, a mindset of a creative technologist characterized by being experimental, inquisitive, and multidisciplinary, and a profound interest in Mixed Reality, spatial design, or immersive visuals. Candidates with experience in MR frameworks such as ARKit/ARCore/WebXR, expertise in procedural content creation (Geometry Nodes, Houdini networks, etc.), familiarity with creative AI workflows like generative visuals and neural rendering, and a public portfolio, GitHub, ShaderToy, or shared custom tools are considered to have additional qualifications that are advantageous for this role. This position was posted by Manasa Kamarthi from Flam.,

As a Deep Learning Engineer, you will be responsible for utilizing cutting-edge Deep Learning techniques to develop advanced algorithms for neural rendering using Python and popular deep learning frameworks. 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 role will involve enhancing the performance of products to ensure high levels of accuracy, speed, and scalability, with guidance from senior team members. Additionally, you will integrate developed software, algorithms, and AI models into our products and services, working collaboratively with stakeholders. It will be your responsibility to maintain the software's security, reliability, and maintainability, following the guidance of senior team members. You will be required to conduct thorough testing and validation to meet the desired performance standards. To qualify for this role, you should hold a Bachelor's or Master's degree in Computer Science, Engineering, or a related field. You should have at least 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, and video synthesis. Experience with self-supervised, few-shot, or zero-shot learning techniques for image synthesis, as well as domain adaptation techniques for face image synthesis, is highly desirable. Moreover, you should have a strong understanding of Generative networks for use-cases like Super-resolution, In painting, etc., and state-of-the-art deepfake algorithms. A minimum of 2 years of relevant experience with generative networks like Transformers, GANs, Auto-encoders, Diffusion models, etc., and at least 1-year experience with Vision Transformers is required. Experience with multi-modal image synthesis with audio-visual data and proficiency in Python programming and deep learning frameworks like PyTorch or TensorFlow are essential, with a minimum of 3 years of experience. Furthermore, 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 are crucial for this role. Candidates with an MS or Ph.D. in Visual Computing, Computer Vision, Machine Learning, or a related field, as well as experience with 3D GANs for human body/face synthesis, will be considered a bonus.,

Utilize cutting-edge deep learning techniques to develop advanced algorithms for neural rendering using Python and popular deep learning frameworks. 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. Enhance the performance of products, ensuring high levels of accuracy, speed, and scalability, with guidance from senior team members. Integrate developed software, algorithms, and AI models into our products and services, working collaboratively with stakeholders. Maintain the software's security, reliability, and maintainability, following senior team members" guidance. Conduct thorough testing and validation to meet the desired performance. Requirements: - 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, and video synthesis. - 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 various use-cases like Super-resolution, Inpainting, etc., and state-of-the-art deepfake algorithms. - Minimum 2 years of relevant experience with generative networks such as Transformers, GANs, Auto-encoders, Diffusion models, etc. - Minimum 1-year 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 Qualifications: - MS or Ph.D. in Visual Computing, Computer Vision, Machine Learning, or a related field. - Experience with 3D GANs for human body/face synthesis.,