Summary :
As part of Apple’s Machine Learning Research organization, we do world-class scientific research and build the technologies that will power future products at Apple.
The ML Research Team does world-class research and development across a wide range of domains including understanding and improving ML, addressing bias and fairness in algorithms, privacy and federated learning, embodied and interactive ML systems, and more.
The techniques and tools we create will impact ML solutions across Apple, which in turn power most of the features we deliver to billions of consumers worldwide.
We are looking for highly motivated, result-oriented engineers with a strong background in ML engineering and software development to join our team.
In this position, you will work with researchers across the Machine Learning Research group to build scalable, distributed training and research pipelines from scratch in the latest and greatest generative models, sequence processing (video, text and speech), federated learning and privacy.
Key Qualifications :
Expert in Python programming, including https : / / github.com / rougier / numpy-100 Expert in at least one ML framework (PyTorch preferred but tensorflow or jax are ok as well)Hands-on experience in implementing ML models and pipelines from scratchExperience with open-source projects and collaborative software developmentExcellent communication skillsExperience and passion to circumvent unexpected roadblocksExperience with CUDA programming, and / or High-Performance Computing and / or distributed computing is a plusPast research experience is a plus
Description :
Work with researchers on the team to build high-performance and scalable software addressing novel ML research algorithms.
Apply solid software engineering skills, leverage experience to deal with the unexpected, explore research software solutions and pave the way to future Machine Learning toolboxes.
Be part of a small team dedicated to advancing ML algorithms and techniques - Is this you? If so we'd love to hear from you.
Additional Requirements :
a public github profile with some examples of prior contributions (preferable)
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