Machine Learning Engineer, Large Visual Generative Model Optimization
The System Intelligence and Machine Learning (SIML) organization at Apple is Looking for visual generative modeling ML engineers to build the next generation of experiences and capabilities in Apple Intelligence. This is an opportunity to join a dedicated core group focusing on the foundational image generation technologies behind Image Playground, Genmoji, Image Wand and Photos Clean Up experiences that shipped as part of Apple Intelligence. We transform the way billions of users express themselves, create and communicate, on Apple platforms! In this role your focus will be on handling the model lifecycle of large visual generative models to enhance both the performance and quality. You will work in a highly multi-functional setting, providing technical leadership, and be responsible for delivering ML solutions.
Selected references to our team’s work:
https://www.apple.com/newsroom/2024/12/apple-intelligence-now-features-image-playground-genmoji-and-more/
https://support.apple.com/guide/iphone/create-genmoji-with-apple-intelligence-iph4e76f5667/ios https://support.apple.com/guide/iphone/create-original-images-with-image-playground-iph0063238b5/ios
We are looking a Machine Learning System Engineers who has a proven background at the intersection of ML optimization and ML model deployment. This would be in service of visual content generation initiatives that form an integral part of Apple Intelligence.
Your primary responsibilities will include:
Designing, implementing, and deploying innovative conditional visual generative models
Overseeing software workflows and test protocols for assembling and deploying visual generative models
Performing R&D in emerging areas of efficient neural network development including quantization, pruning, compression algorithms with a focus on visual generation models.
Handle various components in the model lifecycle of such large visual model, range from training, optimization, deployment, validation, and evaluation.
Effectively communicating results and insights in a highly multi-functional team
- Masters, or Ph.D. in Computer Science, or Computer Engineering; similarly related fields, or comparable professional experience
- Excellent written and verbal communications skills, and have the ability to work hands-on in multi-functional teams
- Strong programming skills in Python or C++
- Proficiency in toolkits like PyTorch or other deep learning frameworks
- Hands on experience training or leveraging larges scale visual generative models (e.g. diffusion models) for real-world user experience and computer vision applications
- Strong background in research and innovation, demonstrated through publications in top-tier journals or conferences, patents, or impactful industry experience. Proven leadership in both applied research and development
- Familiar with model compression algorithms including quantization, pruning, distillations, and experience on optimizing large diffusion models or language models
- Experience with hardware architecture, software & hardware co-design
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