Fall/Winter PhD Machine Learning Research Intern, Computer Vision and Embodied ML
**Fall 2022 OR winter academic term 2023 internship**
Play a part in developing the next generation of core ideas in machine learning. In the Data and Machine Learning Innovation group, we are interested in researching core issues in machine learning, focused on the problems in computer vision and embodied ML. Modern systems have multiple sensors and have to solve wide range of tasks. Hence, multi-modal multi-task problems lie at the core of the challenges we need to solve at Apple. Further, many of our systems are interacting with the real world and users, so that problems in Embodied ML are of high interest.
- Good coding skills in Python and bash scripting. Familiar with workflows for open-source repositories and virtual compute environments.
- Experience in deep learning and related toolkits, e.g. PyTorch, TensorFlow, JAX, etc. a big plus.
- Fast learner and strong motivation on growing and learning new technologies and pushing the frontier of science.
- Good knowledge in machine learning technologies as applied to problems in computer vision and embodied systems.
You will be part of a new team at Apple, focused on long-term machine learning research. Our team is responsible for developing the next generation of ideas powering machine learning innovations at Apple. The role will be very similar to an academic research position — experimenting with new architectures, optimization methods, and open-source datasets with an eye towards submitting this work to a top-tier research conference. This role will entail bootstrapped experimentation, thorough and rigorous analysis of data, and the presentation of new ideas to group meetings to solicit feedback. You are expected to passionate about machine learning research and devising new and impactful ideas. You’re expected to be a collaborative researchers looking to engage others and constantly be learning new ideas. We hope you apply!
Pursuing a Ph.D. in Computer Science, Machine Learning, Computer Vision, Computational Neuroscience, or the equivalent.
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