Data Engineer
4 weeks ago
We're a cutting-edge startup redefining virtual production and video creation using AI, 3D technologies, and real-time rendering. Our platform empowers creators to produce high-quality video content, leveraging advanced neural rendering techniques, generative video, and virtual environments.
Position Overview:
We're seeking a skilled Data Engineer to work at the intersection of synthetic data generation, video processing, and 3D data handling. In this role, you'll be responsible for generating synthetic datasets, processing complex 3D environments, and preparing high-quality data for training neural rendering models and diffusion models.
Key Responsibilities:
Design and implement pipelines to generate synthetic datasets tailored to neural rendering and video generation tasks, with a focus on scalability and realism. Work closely with AI researchers to process 3D video and image data to train diffusion models and neural rendering systems. Develop and maintain data augmentation techniques to enhance the variability and quality of synthetic data used in training. Optimize data pipelines for high-dimensional 3D and video data, ensuring seamless integration with neural network models. Collaborate with the R&D team to create workflows that support real-time data processing for rendering high-quality 3D scenes. Manage data collection, cleaning, and preprocessing to ensure optimal performance in machine learning tasks, with a focus on 3D modeling, camera tracking, and virtual environment rendering. Implement synthetic data generation tools for producing various video scenarios and 3D environments, allowing for enhanced training of generative models.
Qualifications:
Familiarity with 3D data processing, including handling formats like OBJ, FBX, or point clouds. Experience with deep learning frameworks (TensorFlow, PyTorch) and cloud platforms (AWS, GCP, Azure). Proficiency in programming languages such as Python. Excellent problem-solving skills, especially in optimizing data for training machine learning models.
Preferred Skills:
3+ years of experience in data engineering, machine learning data processing, or computer vision. Proven experience with synthetic data generation and data augmentation techniques. Experience with diffusion models, GANs, or neural radiance fields (NeRFs) for generative video tasks. Knowledge of computer graphics and real-time rendering engines (Unreal, Blender) is a plus. Strong understanding of neural rendering techniques, diffusion models, and how large datasets impact their performance.
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