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Camera Software- Sr. Machine Learning Research Engineer
Apple
H1B ✓On-sitesenior levelPosted April 23, 2026
About the Role
Design and implement novel generative model architectures and training strategies for computational photography applications. Develop scalable data pipelines and comprehensive evaluation frameworks to assess model performance and research directions.
Requirements
Requires a PhD or MS degree with significant industry experience in computer vision and deep learning. Candidates must have a strong foundation in image processing and proven experience developing generative models.
Full Job Description
iPhone is the most popular camera in the world. The flawless integration of software and hardware has led to features like Memories and Portrait Mode which deliver experiences that are magical. The Camera & Photos team focuses on user-experience by using computer vision and image processing through machine learning. Our team works hard on products that ship to millions of people. We are looking for people who want to do the same.
The Computational Imaging team develops the camera pipelines and innovative algorithms for Apple’s mobile devices, including the iPhone and iPad. Combining innovative algorithms with optimized implementations, our team delivers the quality and features which help to re-define mobile photography. In this role, you will work hands-on with diffusion models, transformers and next-gen generative techniques, while collaborating closely with product, design and research teams to bring your ideas to life. If you are passionate about inventing and developing new imaging algorithms to improve the photography experience, we would like to hear from you.
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.
Description
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.
Minimum Qualifications
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.
Preferred Qualifications
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.