AIML - Senior Machine Learning Research Scientist, Biosignals Intelligence Group
Cupertino, California, United States
Machine Learning and AI
The Biosignals Intelligence Group is at the forefront of pioneering novel sensing technologies, machine learning innovation, and building health and human-computer interaction technologies at Apple. We are a fundamental and applied research-focused team with diverse backgrounds focused on creating innovative technologies and experiences for millions of users. We are looking for a research scientist passionate about solving real-world problems in the health/wellness domain that will translate to novel experiences and technologies benefitting our customers.
Key Qualifications
- Strong background in audio/speech signal processing, feature extraction, and analyses
- Hands-on experience with building novel state-of-the-art machine learning algorithms and expertise on dealing with large datasets, strongly desired
- Background in foundation models (FMs), large language models (LLM), and generative modeling approaches
- Prior experience on multi-modal machine learning, representation learning and on-device modeling capabilities using modern machine learning packages (e.g. PyTorch, TensorFlow)
- Passionate about applying machine learning methods to deliver end-user experiences in health/wellness space
- Strong publication record in the field of speech/audio signal processing, Machine Learning or AI is highly desirable, indicating an ability to not only understand but also contribute to cutting-edge research
- Experience with building multi-modal information retrieval systems, prototyping, and deployment
- Excellent interpersonal and communication skills and a strong team player
Description
In this role, you will use your skills and experience in state-of-the-art machine learning and deep learning to design, implement and evaluate new machine learning models and algorithms to solve complex and challenging problems involving multimodal data and unique objectives. You will have the opportunity to explore and develop novel generative AI technologies and investigate and explore foundation models. The ability to substantially improve model performance from a prototype by leveraging novel architectures, optimizing hyper-parameters or exploring data augmentation techniques is key.
Education & Experience
Ph.D. in Electrical/Computer Engineering, Computer Science, Machine Learning, or related fields or an equivalent qualification obtained through other avenues.