Senior ML Software Engineer - Apple Watch at Apple

Cupertino, California, United States -

Full Time

Start Date

Immediate

Expiry Date

22 Jan, 26

Salary

0.0

Posted On

24 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, Deep Learning, PyTorch, TensorFlow, Swift, Objective-C, Statistical Analysis, Predictive Modeling, Time-Series Data, Collaboration, Algorithm Optimization, User Experience, Data Collection, Model Training, Model Deployment

Industry

Computers and Electronics Manufacturing

Description

Imagine what you could do here. At Apple, new ideas have a way of becoming great products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish! 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 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, you’ll 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: - Develop 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 behavior - Integrate and deploy ML models on-device, building power-efficient frameworks that encapsulate models, interface seamlessly with sensors, and communicate effectively with UX layers - Drive innovation from concept to deployment, ensuring promising research ideas evolve into high-impact, user-facing features - Design and implement tools, analytics, and processes to perform in-depth, hands-on analysis for validating and quantifying algorithm performance both offline and on-device MINIMUM QUALIFICATIONS M.S. or Ph.D. in Machine Learning, Computer Science, or a related field Solid knowledge of machine learning methods, statistical analysis, and predictive modeling using time-series data Strong Python skills with experience writing production-quality code and working with deep learning frameworks such as PyTorch or TensorFlow Experience with Swift or Objective-C and developing on Apple platforms Excellent communication and collaboration skills, with ability to work independently or in small teams PREFERRED QUALIFICATIONS Proficient in the full ML development cycle: data collection, model training and optimization, defining metrics, evaluation, performing failure analysis, and model deployment to resource constrained devices

Responsibilities

Develop and optimize machine learning algorithms using multimodal sensor data to enhance understanding of user activities. Collaborate with cross-functional teams to drive innovation from concept to deployment of new features for Apple Watch.