
Senior Software Engineer, Applied ML - Watch Software
Seattle, WAFull-timeSeen 1 day agoSeen in employer's feed 1 day ago
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At a glance
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Job overview
Apple’s team develops sensing and machine-learning technologies for Apple Watch and other products, creating features such as DoubleTap, AssistiveTouch, Handwashing, and Raise to Speak. The Software Engineer will work across disciplines, from modeling pipelines and on-device prototyping to productization, collaborating with research and product teams to explore experiences and ship features.
Skills & qualifications
Skills
Qualifications
Full job description
Weekly Hours: 40
Role Number: 200691400-3337
Summary
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
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5+ years of professional software development experience.
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Expertise using Swift to develop on Apple platforms.
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Familiarity with Python and numerical processing libraries (NumPy, Matplotlib, pandas) for time series analysis.
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Strong communication and collaboration skills, with the ability to work independently or in small teams.
Preferred Qualifications
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M.S. in Computer Science, Machine Learning, or a related field.
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Knowledge of machine learning methods and statistical analysis.
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Experience building scalable modeling pipelines for data processing, training, and evaluation.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
How this job compares
Set against the 7,944 open Software Engineering jobs on Olive Jobs, counted October 30, 2026.
- Pay
- This postingNot listed
- Washington median$168–254K/yr373 salary ranges
- Washington median$45–51/hr26 hourly ranges
- Openings
- Olive Jobs lists 450 open Software Engineering jobs in Washington and 7,944 across the US. 7% of them nationwide are listed as remote or flexible.
- Hiring the most in Washington
- Microsoft Corporation68 open
- Amazon56 open
- Google34 open
- Experience
- This posting asks for at least 5 years of experience; Software Engineering postings that state a minimum ask for 7 years at the median (6,138 postings).
- Education
- 2,188 of the 7,944 open Software Engineering jobs (28%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on October 30, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
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