Applied Research Scientist - Apple Health
Seattle, Washington, United States
Machine Learning and AI
We are looking for applied scientists with a passion for using machine learning to transform in-the-wild sensor data from the most worn wearable device into intelligent health experiences. You will join a close-knit team of highly accomplished and deeply technical researchers and engineers focused on delivering groundbreaking machine learning technologies to the health space. As a member of this team, you will use your practical knowledge and experience with data science, machine learning, and artificial intelligence techniques to tackle important technical problems to deliver the next generation of Apple health experiences. You will play a key role in defining, designing, implementing, and evaluating new machine learning models and algorithms for significant problems involving complex data and objectives. In this role, you will collaborate with highly innovative product teams across Apple, and see projects through to deployment on 1 billion Apple devices worldwide.
- Expertise in at least one area of machine learning, artificial intelligence, or statistics (e.g., health, time series, causal inference, probabilistic modeling, bandits and reinforcement learning, deep learning, optimization, NLP)
- Strong interest in applying machine learning to health related problems and data
- Ability to distill vague product experiences into concrete problem definitions
- Experience using a programming language (Python, R, C/C++) for machine learning or a statistical computer language (R, Python, SQL) to manipulate data and draw insights from large data sets.
- A drive to learn and master new technologies and techniques
- A passion for making methods robust and scalable
- Excellent verbal and written communication and presentation skills
- 3–5 years of practical experience applying ML to solve real-world problems or relevant quantitative and qualitative research and analytics experience
Responsibilities * Investigating innovative machine learning, artificial intelligence, and statistics techniques for health data challenges * Designing and implementing machine learning pipelines * Modeling complex problems, discovering insights, and identifying opportunities through the use of statistical, algorithmic, and visualization techniques * Processing, cleaning, and verifying the integrity of data used for analysis * Validating your findings using an experimental and iterative approach and effectively presenting back your findings Preferred Qualifications 5+ years of practical experience applying ML and/or data science to tackle real-world problems, especially in the health domain Proficiency training large scale models using modern machine learning packages (e.g. TensorFlow, PyTorch, autograd), and experience with data analysis stacks (such as NumPy, SciPy, pandas, Spark, etc.) Strong fundamentals in problem solving, algorithm design, and model building Passion for creating new technologies with high product impact
Education & Experience
MS or PhD in Computer Science, Machine Learning, AI, Statistics, Mathematics, or related quantitative field Professional certifications