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Machine Learning Engineer
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Machine Learning Engineer
- San Diego, California, United States
- San Diego, California, United States
À propos
Description This role is ideal for an engineer who enjoys moving quickly from idea to prototype to product, creatively overcoming data limitations, and applying new tools to multi-modal sensor fusion problems in health and wellness. You will work across the full algorithm lifecycle including data strategy, modeling, evaluation, optimization, and deployment.
Responsibilities
Develop and validate ML and GenAI-driven algorithms for health sensing applications from concept through productization
Prototype and compare multiple approaches using real and synthetic data to accelerate algorithm development
Design experiments and evaluation methodologies to quantify performance and guide algorithm improvements
Optimize algorithms for robustness, efficiency, and on-device deployment constraints
Work cross-functionally with user studies, hardware, software, and product teams to bring algorithms into product
Analyze failure modes, quantify tradeoffs, and drive data-driven algorithm improvements
Minimum Qualifications
Bachelors degree in Computer Science, Electrical Engineering, Biomedical Engineering, Statistics, Applied Mathematics, or related field, or equivalent industry experience.
Strong foundation in machine learning, statistics, signal processing, or applied mathematics for real-world sensing problems
Experience applying modern AI techniques, including generative AI and agentic AI, to accelerate algorithm development, data generation, and performance evaluation
Proficiency in Python for algorithm development and optimization
Demonstrated ability to rapidly prototype, evaluate multiple approaches, and iterate based on experimental results
Experience owning algorithm development from early exploration through validation and integration
Preferred Qualifications
Experience developing algorithms for physiological sensing using multi-modal data
Familiarity with on-device ML frameworks or resource-constrained optimization
Experience working with incomplete, noisy, or limited datasets
Background in experimental design and statistical validation
Experience with distributed or cloud-based ML workflows
Experience accelerating development through simulation, synthetic data, or creative data augmentation approaches
Self-driven, curious engineer comfortable taking ambiguous sensing problems from concept to working solutions
Compensation and Benefits Apple’s base pay range for this role is between $139,500 and $258,100, and will depend on skills, qualifications, experience, and location.
Apple employees may become shareholders through discretionary stock programs, restricted stock units, or a discounted Employee Stock Purchase Plan. Benefits include comprehensive medical and dental coverage, retirement plans, discounted products and services, and education reimbursement for qualified courses.
The role may be eligible for bonuses, commissions, and relocation assistance. Learn more about Apple benefits.
Location eligibility and program terms apply.
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. Learn more about your EEO rights as an applicant.
Apple accepts applications to this posting on an ongoing basis.
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Compétences linguistiques
- English
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