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Description
We are hiring a software engineer to work on a new initiative that will push the boundary of what's possible in the field of Generative AI. The ideal candidate will have deep knowledge in computational photography and multi-modal image editing. This position requires a self-motivated individual with excellent interpersonal skills to effectively collaborate with all levels of the organization.
Minimum Qualifications
MS or PhD in Computer Science, Machine Learning or related field, and 5+ years of significant industry experience delivering products using state-of-the-art computational photography and machine learning technologies. Extensive knowledge in theory and practice of machine learning and deep learning techniques, particularly diffusion models, variational auto-encoders and transformers. Experience delivering customer-facing products with computer vision, computational photography or generative AI features. Hands-on experience building, training, evaluating, and deploying diffusion, transformer and Generative Adversarial Network based models, or related methods. Experience contributing to large codebases while delivering high-quality software at scale. Strong programming skills in high-level languages like Python and one of the deep learning toolkits such as PyTorch, JAX, or TensorFlow. Ability to collaborate effectively across organizations and drive alignment in large cross-functional projects. Ability to concisely communicate with audiences of different backgrounds, from non-technical individuals to experts in the field. Committed to encouraging an open and inclusive work environment.
Preferred Qualifications
Experience optimizing models and algorithms that run efficiently on resource-constrained platforms is a plus. Experience with flow matching and multi-modal conditioning for generative modeling is a plus. Familiarity with 3D reconstruction techniques from single or multiple images, particularly ML-based methods, is a plus. Knowledge of and keen interest in the art and science of photography and aesthetics. Publications at major conferences (CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR) is a plus.
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