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Apple is seeking a passionate ML researcher to contribute to long-term, curiosity‑driven projects across LLMs, VLMs and generative foundation models. You will propose and execute research plans, implement experiments, and publish results to advance our understanding of AI.
You will collaborate with cross‑functional teams, mentor colleagues, and communicate findings through technical reports and talks, helping shape the future of Apple's products and platforms.
Play a part in building the next revolution of machine learning technology. We're looking for a passionate researchers to work on ambitious curiosity driven long-term research projects that will impact the future of Apple, and our products. In this role, you'll have the opportunity to work on innovative foundational research in machine learning focusing on LLMs, VLMs, and more generally generative foundation models, possibly at all steps (pre-training, fine-tuning, steering, efficient inference etc…)
You have a strong research background in machine learning or related fields, and regularly publish your results in the main relevant conference and journal venues, and make sure that your research results are reproducible. You will propose your own research plan to advance our understanding of machine learning and execute it through implementation and experimentation, in collaboration with your colleagues. You will provide technical mentorship and guidance, and prepare technical reports for publication and conference talks. You will have the opportunity to collaborate with broader teams across Apple
At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.
At Apple, we believe accessibility is a fundamental human right. You'll find that idea reflected in everything here - in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
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Role Number: 200619263-2911