Machine Learning Intern - Generative Ai

Application Deadline - Sunday 16th November Are you interested in developing products that use machine learning and computer vision in novel and interactive ways? Want to harness your skills to build groundbreaking features like Image Generation, Smart Script, or Scribble? Envision yourself building high-impact products powered by generative models, reaching hundreds of millions of users? We are an applied machine learning team based in Zurich, Switzerland, searching for a motivated intern to help advance the future of machine learning models to power products around text and freeform drawing recognition and generation. You will get the opportunity to work closely and collaborate with a variety of teams across Apple.

Description

As an intern in our team, you'll directly influence the future by investigating new ideas destined for our next-generation products. You'll concentrate on researching modeling techniques to tackle key machine learning challenges that underpin future features. We're looking for an intern to prototype innovative models and contribute to the project's overall research and design. The ideal candidate will have experience with computer vision, speech recognition, deep learning, and/or other applications of machine learning systems.

Responsibilities

• Assist in crafting and implementing machine learning model architectures using standard machine learning frameworks (PyTorch, Jax, Tensorflow)
• Design and perform experiments to optimize machine learning model behavior
• Explore novel approaches to solving problems with ML models
Document your work and your findings

Minimum Qualifications

• Currently enrolled in a Master's degree program (or higher, or equivalent) in a related field.
• Experience with common Generative AI and machine learning concepts
• Hands-on experience working with Python and deep learning toolkits such as PyTorch and Jax.

Preferred Qualifications

• Familiarity with diffusion models
• Familiarity with machine learning experiment design and training pipeline development
• Ability to work in a supportive environment
• Experience in building products or end-to-end prototypes around ML models.
Proven expertise in machine learning supported by a strong publication record in relevant conferences (e.g. NeurIPS, ICML, ICLR, AISTATS, CVPR, ICCV, ECCV, ICASSP, InterSpeech, AAAI, ACL, FAccT).

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