We are looking for an applied research scientist with a passion for developing and using machine learning to transform sensing data from the most worn wearables and devices into intelligent health experiences. You will join a close-knit team of highly accomplished and deeply technical research scientists and engineers focused on delivering cutting edge machine learning technologies to the health space.
As a member of this team, you will have the opportunity to use your deep understanding of machine learning, artificial intelligence, and data science to solve challenging technical problems and deliver the next generation of Apple health experiences. You will perform applied research by defining, designing, implementing, and evaluating new machine learning models and algorithms to solve challenging problems involving unique data and objectives. In this role, you will collaborate with highly innovative product teams across Apple, and see projects through to deployment on over 1 billion Apple devices worldwide.
The candidate must have demonstrated expertise working with real data in one of the following core areas:
-Optimization (with experience in discrete optimization)
-Multimodal time series analysis
Demonstrated interest — via publications or products — in applying machine learning methods to health related problems and data.
Ability to distill vague product experiences into concrete problem definitions.
A demonstrated passion for making methods robust, fair, private, efficient, and scalable.
Skilled in explaining and presenting analyses and machine learning concepts to a broad technical audience.
Proficiency developing machine learning solutions using Python and its associated ecosystem — numpy, pandas, TensorFlow, PyTorch, etc. — or other programming language.
Provide , upon request during the actual interview process, 3–5 strong recommendation letters supporting the above mentioned key qualifications
Your responsibilities include:
Researching, developing, and implementing the most innovative machine learning techniques mentioned under Key Qualifications applied to unique health data and problems.
Actively engaging with the academic community by publishing papers and presenting your work.
Transferring machine learning solutions to data scientists and engineers on product teams.
Providing technical guidance to product teams on the machine learning approaches appropriate for a task.
Education & Experience
PhD in machine learning/data sciences (CS, ECE, Statistics, Operations Research, Math, Economics, or other related fields).
2+ years of research experience in academia or industry after the PhD (summer internships could be considered as experience).
Publications in the leading venues for the candidate’s area of expertise from the ones mentioned under Key Qualifications.
Demonstrated abilities in problem formulation, algorithm design, and model building, including statistical analysis and evaluation.
Passion for creating new technologies with high product impact.
Excellent verbal and written communication and presentation skills.
Having recommendation letters both from Academia and industry
Role Number: 200428568