Camera Software - Machine Learning Research Engineer
Apple
Camera Software - Machine Learning Research Engineer
Job Description
Phone 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 redefine 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 the latest research in generative AI, computer vision, and computational photography. Translate findings into practical applications.
Locations
- Cupertino, California, United States 95014
Salary
Estimated Salary Rangemedium confidence
25,000,000 - 60,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- computer visionintermediate
- image processingintermediate
- machine learningintermediate
- diffusion modelsintermediate
- transformersintermediate
- generative techniquesintermediate
- designing novel generative model architecturesintermediate
- developing training strategiesintermediate
- fine-tuning pre-trained modelsintermediate
- adapting models for specific use casesintermediate
- building scalable data pipelinesintermediate
- developing evaluation frameworksintermediate
- implementing quantitative metricsintermediate
- qualitative analysis methodologiesintermediate
- conducting ablation studiesintermediate
- hyper-parameter optimizationintermediate
- deep technical analysisintermediate
- identifying research directionsintermediate
- code reviewsintermediate
- technical discussionsintermediate
- knowledge sharingintermediate
- communicating complex technical conceptsintermediate
- clear documentationintermediate
- presentationsintermediate
- staying current with research in generative AIintermediate
- translating findings into practical applicationsintermediate
- collaborating with product teamsintermediate
- collaborating with design teamsintermediate
- collaborating with research teamsintermediate
Required Qualifications
- Expertise in image processing, computer vision, and deep learning. (experience)
- Strong experience with deep learning frameworks (e.g. PyTorch) and modern ML toolchains. (experience)
- Hands-on with multi-GPU/multi-node/distributed training and large-scale experimentation. (experience)
- MS + 5 years industry experience. (experience, 5 years)
Preferred Qualifications
- Proven experience with training and developing generative models. (experience)
- Excellent communication skills and an ability to bridge gap between technical depth and product impact. (experience)
- Collaborative mindset with openness to feedback and continuous learning. (experience)
- Curiosity-driven with a track-record of identifying and solving complex technical problems. (experience)
- Publications at major conferences (CVPR, ICCV, NeurIPS, ICML) or open-source contributions would be a plus. (experience)
Responsibilities
- 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 the latest research in generative AI, computer vision, and computational photography. Translate findings into practical applications.
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Camera Software - Machine Learning Research Engineer
Apple
Camera Software - Machine Learning Research Engineer
Job Description
Phone 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 redefine 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 the latest research in generative AI, computer vision, and computational photography. Translate findings into practical applications.
Locations
- Cupertino, California, United States 95014
Salary
Estimated Salary Rangemedium confidence
25,000,000 - 60,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- computer visionintermediate
- image processingintermediate
- machine learningintermediate
- diffusion modelsintermediate
- transformersintermediate
- generative techniquesintermediate
- designing novel generative model architecturesintermediate
- developing training strategiesintermediate
- fine-tuning pre-trained modelsintermediate
- adapting models for specific use casesintermediate
- building scalable data pipelinesintermediate
- developing evaluation frameworksintermediate
- implementing quantitative metricsintermediate
- qualitative analysis methodologiesintermediate
- conducting ablation studiesintermediate
- hyper-parameter optimizationintermediate
- deep technical analysisintermediate
- identifying research directionsintermediate
- code reviewsintermediate
- technical discussionsintermediate
- knowledge sharingintermediate
- communicating complex technical conceptsintermediate
- clear documentationintermediate
- presentationsintermediate
- staying current with research in generative AIintermediate
- translating findings into practical applicationsintermediate
- collaborating with product teamsintermediate
- collaborating with design teamsintermediate
- collaborating with research teamsintermediate
Required Qualifications
- Expertise in image processing, computer vision, and deep learning. (experience)
- Strong experience with deep learning frameworks (e.g. PyTorch) and modern ML toolchains. (experience)
- Hands-on with multi-GPU/multi-node/distributed training and large-scale experimentation. (experience)
- MS + 5 years industry experience. (experience, 5 years)
Preferred Qualifications
- Proven experience with training and developing generative models. (experience)
- Excellent communication skills and an ability to bridge gap between technical depth and product impact. (experience)
- Collaborative mindset with openness to feedback and continuous learning. (experience)
- Curiosity-driven with a track-record of identifying and solving complex technical problems. (experience)
- Publications at major conferences (CVPR, ICCV, NeurIPS, ICML) or open-source contributions would be a plus. (experience)
Responsibilities
- 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 the latest research in generative AI, computer vision, and computational photography. Translate findings into practical applications.
Tags & Categories
Answer 10 quick questions to check your fit for Camera Software - Machine Learning Research Engineer @ Apple.
10 Questions
~2 Minutes
Instant Score
Related Books and Jobs