Synthetic Visual Data Engineer (Simulation & Domain Randomization)
We are seeking a talented Synthetic Visual Data Engineer (Simulation & Domain Randomization) to join our innovative team. In this role, you will be responsible for the development and enhancement of synthetic data generation processes, specifically focusing on simulation and domain randomization techniques. Your work will contribute to the advancement of machine learning models, particularly in the fields of computer vision and robotics. You will design and implement robust simulation environments, ensuring that the generated data is diverse, realistic, and suitable for training state-of-the-art algorithms.
Your key responsibilities will include collaborating with cross-functional teams to define data requirements, developing synthetic data generation pipelines, and optimizing existing simulation frameworks. You will also conduct experiments to validate the effectiveness of domain randomization strategies, analyzing the impact on model performance and generalization. Moreover, you will be expected to stay abreast of the latest research and advancements in synthetic data generation and contribute to the ongoing improvement of our methodologies.
The ideal candidate will possess a strong background in computer graphics, computer vision, or a related field, along with proficiency in programming languages such as Python and C++. Familiarity with simulation tools such as Unity, Unreal Engine, or similar platforms is essential. A solid understanding of machine learning principles, particularly in relation to training neural networks, is highly advantageous. If you are passionate about pushing the boundaries of synthetic data and are eager to make a significant impact in the world of AI, we encourage you to apply and join us in shaping the future of technology.
Synthetic Visual Data Engineer (Simulation & Domain Randomization)
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