Summary
Posted: Oct 30, 2019
Role Number:200118126
We are looking for software engineer with a passion for building systems for deep learning: making deep learning more efficient, s...Summary
Summary
Posted: Oct 30, 2019
Role Number:200118126
We are looking for software engineer with a passion for building systems for deep learning: making deep learning more efficient, scalable and easy to use at Apple. We are a close-knit team in of highly accomplished, deeply technical engineers building fundamental technologies that empowers researchers and engineers to deliver amazing intelligent user experiences in Apple products and services.
As a member of this team, you will apply your knowledge and experience in deep learning systems, high performance computing, numerical optimization, and compilers to build the next generation deep learning systems. You will play a key role in developing:
* 1) a distributed system for highly scalable and efficient training of deep learning models
* 2) a compiler/inference framework for easily deploying complex models to a diverse set of Apple devices with hardware acceleration
You will collaborate with innovative product teams across Apple, including CoreML, Siri, Cameras and Photos (think Face ID), and see projects through deployment on 1 billion Apple devices worldwide. You will have the opportunity to contribute to every cool project around Apple and transfer your ideas into solutions for some of the most challenging technical problems in the next generation of Apple products. You will have the opportunity to share your work with open source community through Apple's increasing open source participation (think CoreML).
Key Qualifications
If you're an experienced engineer with passion for bringing the next generation of deep learning-enhanced experiences to billions of devices, we'd love to hear from you.
Qualities the team would find especially useful include:
1. Expertise in one or more of the following:
1. Design and implementation of ML libraries and/or compilers for deep learning
2. Performance optimization: software optimization for CPU (multithreaded program), hardware accelerator (GPU, FPGA), or distributed high performance computing
3. Continuous integration/deployment and cloud integration
4. Distributed non-convex optimization
2. Proficiency in training and deploying large scale models using modern machine learning frameworks (e.g. TensorFlow, PyTorch)
3. Passion for exploring and adopting new technologies
4. Excellent verbal and written communication and presentation skills
5. Focus on creativity, collaboration, and innovation
Education & Experience
MS/PhD in Machine Learning
BS/MS/PhD in Computer Science or Electrical Engineering
Solid industry experience
Additional Requirements
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