Senior Software Engineer, Applied ML - Watch Software
Confirmed on the employer's own hiring board on Oct 30, 2026. First seen by Alion on Oct 27, 2026. Apple scores A on the Alion truth index.
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 devices.
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 team.
Come join us and build the future!
Description
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 features.
We are looking for a versatile 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 building scalable modeling pipelines to rapid on-device prototyping and full-scale productization.
Minimum Qualifications
5+ years of professional software development experience.
Expertise using Swift to develop on Apple platforms.
Familiarity with Python and numerical processing libraries (NumPy, Matplotlib, pandas) for time series analysis.
Strong communication and collaboration skills, with the ability to work independently or in small teams.
Preferred Qualifications
M.S. in Computer Science, Machine Learning, or a related field.
Knowledge of machine learning methods and statistical analysis.
Experience building scalable modeling pipelines for data processing, training, and evaluation.