Jobs / App***
Senior ML Software Engineer - Apple Watch
App*** · Boulder, CO, United States
Visa sponsorship details are locked. Unlock company name and apply link with .
Boulder, CO, United States175,000-308,500 USD/yearlyHybrid
Remuneration
175,000-308,500 USD/yearly
Location
Boulder, CO, United States
Visa sponsorship
Sponsors visa
Job 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.
Benefits
At Apple, base pay is one part of our total compensation package and is determinThis provides the opportunity to progress as you grow and develop within a role.The base pay range for this role is between $175,000 and $308,500, and your baseIncluding: Comprehensive medical and dental coverage, retirementAdditionally, this role might be eligible for discretionary bonuses or commissioLearn more about AppleNote: Apple benefit, compensation and employee stock programs are subject to eli
Qualifications
- We prototype new experiences, develop and ship products, and publish our work.
- You collaborate effectively with cross-functional partners
- You have a deep commitment to product quality and interest in building consumer applications
- Excellent communication and collaboration
- or Ph.
- 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
- experience, and location.
- App*** employees also have the opportunity to become an App*** shareholder through participation in App***'s discretionary employee stock programs.
- App*** employees are eligible for discretionary restricted stock unit awards, and can purchase App*** stock at a discount if voluntarily participating in App***'s Employee Stock Purchase Plan.
- You'll also receive
Responsibilities
- The team you will join is responsible for creating the
- 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
Skills
Communication
Degrees
AssociatePhD
Industry
EducationEnergy
Relocation
Yes