Senior Software ML Engineer Watch Software

Our team is working toward a future where our devices are aware of us and our environment they directly support our health and wellbeing and they nudge us to be more thoughtful present and inspired human beings. We believe there is huge opportunity to improve lives and the world by understanding people our activities connections and the environments we live in using sensing and machine learning on our team works with cross-functional partners across Apple to create high-impact features and new ways to interact on Apple Watch home products and new hardware. We prototype new experiences develop and ship products and publish our work. We are a creative multi-disciplinary optimistic and collaborative join us and build the future!

The team you will join is responsible for creating the technologies that power new innovative product features for Apple Watch like DoubleTap AssistiveTouch Handwashing and Raise to Speak. We are highly collaborative and partner with a variety of research and product teams across Apple to explore novel experiences and ship are looking for a versatile Machine Learning Software Engineer who is passionate about developing innovative ML-driven product features that push the boundaries of sensing and human-computer interaction and who can work across disciplines from training advanced models to rapid on-device prototyping and full-scale productization.

In this hybrid role youll collaborate closely with designers ML engineers and software experts to transform ambitious loosely defined ideas into next-generation sensing experiences that reach millions of Apple Watch users worldwide. Your responsibilities will include:nnDesign implement and ship new ML-powered features on and deploy ML models on-device building Swift or Objective-C frameworks that encapsulate models interface with sensors and communicate with UX and optimize code for the performance and power constraints unique to Apple and optimize ML algorithms leveraging multimodal sensor data like motion and audio to detect user activities and contextual situations that enhance our understanding of real-world and implement tools analytics and processes to perform in-depth hands-on analysis for validating and quantifying algorithm performance both offline and innovation from concept to deployment ensuring promising research ideas evolve into high-impact user-facing features.n

M.S. or Ph.D. in Computer Science Machine Learning or a related with Swift or Objective-C and developing on Apple using Python and deep learning frameworks such as PyTorch or TensorFlow for predictive communication and collaboration skills with ability to work independently or in small teams.n

Experience optimizing and profiling applications for performance and power to work within the full ML development cycle: data collection model training and optimization defining metrics evaluation performing failure analysis and model deployment to resource constrained devicesn