Large Machine Learning Model Optimization Engineer
1 week ago
We are seeking a highly skilled Machine Learning Model Optimization Engineer to join our team at Apple. As a key member of our applied research and engineering team, you will be responsible for developing and optimizing real-time on-device Language, Computer Vision, and Machine Perception technologies across Apple products.
Our team focuses on technology research and development to deliver Apple quality, state-of-the-art experiences. We pride ourselves on innovating through the full stack, and partnering with HW, SW and ML teams to influence the sensor and silicon roadmap that brings our vision to life.
As a Machine Learning Model Optimization Engineer, you will have the opportunity to be at the forefront of technological advancements and contribute to the successful shipping and delivery of Apple intelligence.
Responsibilities- Implement and deliver various optimization techniques that improve the performance of large language and diffusion models on devices.
- Collaborate with a diverse range of organizations within Apple to drive the development of the on-device Apple Intelligence LLM and diffusion model developments.
- Define and lead the execution of model compression, distillation, and integrating to the full Apple Intelligence user experiences.
- Develop and maintain efficient ML model development experiences and a passion for shipping machine learning models on device.
- Software engineering skills in Python.
- Experience in developing large computer vision and machine learning models, particularly on the hardware-aware model optimizations.
- BS and a minimum of 10 years relevant industry experience.
- Familiar with model compression algorithms including quantization, pruning, distillations, and experience on optimizing large diffusion models or language models.
- MS or PhD degree in Computer Science, or equivalent industry research experience.
- Experience with hardware architecture, software & hardware co-design.
- Leadership experience in driving large-scale projects in the industry.
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