Camera Software- Sr. Machine Learning Research Engineer

Design novel generative model architectures and training strategies for vision and computational photography applications. Fine-tune and adapt pre-trained models for specific use cases and domains. Build scalable and robust data pipelines for large-scale image and video datasets. Develop comprehensive evaluation frameworks including implementing quantitative metrics and qualitative analysis methodologies, conducting ablation studies and hyper-parameter optimization, for model performance assessment. Conduct deep technical analysis and identify research directions. Participate in code reviews, technical discussions and knowledge sharing sessions. Communicate complex technical concepts through clear documentation and presentations. Stay current with latest research in generative AI, computer vision and computational photography. Translate findings into practical applications. PhD or MS + 3 years industry experience. Solid foundation in image processing, computer vision and deep learning fundamentals. Academic or project experience with image/video generation models. Minimum PhD + 2 years or MS + 5 years industry experience. Expertise in image processing, computer vision and deep learning. Strong experience with deep learning frameworks (e.g. PyTorch) and modern ML toolchains. Proven experience with training and developing generative models. Hands-on with multi-GPU/multi-node/distributed training and large-scale experimentation. Curiosity-driven with a track-record of identifying and solving complex technical problems. Excellent communication skills and an ability to bridge gap between technical depth and product impact. Collaborative mindset with openness to feedback and continuous learning. Publications at major conferences (CVPR, ICCV, NeurIPS, ICML) or open-source contributions would be a plus.

For more details click Job Post.