Design novel generative model architectures and training strategies for vision and computational photography -tune and adapt pre-trained models for specific use cases and scalable and robust data pipelines for large-scale image and video comprehensive evaluation frameworks including implementing quantitative metrics and qualitative analysis methodologies conducting ablation studies and hyper-parameter optimization for model performance deep technical analysis and identify research directions. Participate in code reviews technical discussions and knowledge sharing complex technical concepts through clear documentation and current with the latest research in generative AI computer vision and computational photography. Translate findings into practical applications.
Expertise in image processing computer vision and deep learning.
Strong experience with deep learning frameworks (e.g. PyTorch) and modern ML toolchains.
Hands-on with multi-GPU/multi-node/distributed training and large-scale experimentation.
MS 5 years industry experience.
Proven experience with training and developing generative models.
Excellent communication skills and an ability to bridge gap between technical depth and product impact.
Collaborative mindset with openness to feedback and continuous learning.
Curiosity-driven with a track-record of identifying and solving complex technical problems.
Publications at major conferences (CVPR ICCV NeurIPS ICML) or open-source contributions would be a plus.
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