Machine Learning Applied Researcher Speech, Vision and Audio

Imagine what you could do here. At Apple new ideas have a way of becoming extraordinary products services and customer experiences very quickly. Bring passion and dedication to your job and theres no telling what you could accomplish. Dynamic smart people and inspiring innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same passion for innovation that goes into our products also applies to our practices strengthening our commitment to leave the world better than we found it. Join us to help deliver the next groundbreaking Apple product. Do you love working on challenges that no one has solved yet As a member of our dynamic group you will have the unique and rewarding opportunity to craft upcoming products that will delight and inspire millions of Apples customers every single day.

We are looking for a talented and experienced applied ML researcher who can both research new capabilities and develop frontier models using cutting-edge this role you will take on high-risk high-reward challenges - researching designing and improving state-of-the-art deep learning models trained on unique data implementing novel machine learning algorithms and developing solutions to problems that dont have obvious answers. Your scope will encompass various ML subfields and modalities combining ideas from different fields to solve unique challenges and deliver solutions adopted broadly across teams.

Research and develop cutting-edge deep learning models and algorithms leveraging multiple data modalities (e.g. vision audio sensor text).nDesign and implement novel neural network architectures solving unique challenges in the field of ambiguous problem spaces - formulate hypotheses run experiments learn from negative results and iterate toward model performance while maintaining awareness of deployment constraints such as latency memory and across teams synthesizing approaches from different fields into solutions that work with and benefit the entire findings clearly to stakeholders and team current with scientific literature on frontier ML methods and identify opportunities to apply new ideas.

BS in Computer Science Electrical Engineering or a related field - or equivalent practical in academic or industry working with Pytorch.

MS or PhD in Computer Science Electrical Engineering or a related field with 10 years of relevant industry foundation in deep learning theory and hands-on experience training large-scale knowledge in one or more of: self-supervised learning synthetic data generation large language model training or automatic speech working with multimodal data (e.g. images audio time-series or sensor fusion).nStrong analytical and problem-solving skills; ability to translate research ideas into production-quality and persistence - comfort with experimentation cycles where many attempts fail before one record at top-tier ML venues (NeurIPS ICML ICLR Interspeech ICASSP etc.).nMultidisciplinary background spanning fields such as neuroscience physics signal processing or mathematics. Experience collaborating with distributed teams across time zones.