Machine Learning Engineer - Crowdsourced Sensing

Machine Learning Engineer - Crowdsourced Sensing

Cupertino, California, United States Software and Services

The Sensing and Connectivity team is committed to developing innovative technology that enhances user safety and makes our devices more intelligent. We are exploring how the incredible sensing, processing, and connectivity of iPhone can be leveraged to detect nearby hazards and deliver timely alerts. We are seeking a Machine Learning Engineer to own the design, deployment, and operation of ML models that run across heterogeneous mobile and edge devices.

In this role, you will build production ML systems end-to-end including feature design, training, on-device inference, monitoring, and continuous improvement based on real-world telemetry.

As a Machine Learning Engineer on the crowdsourced sensing team, you will develop, deploy, and maintain machine-learning models that operate reliably in noisy, real-world environments and at global scale.

• Own ML models end-to-end, including feature design, training, evaluation, deployment, and iteration based on live telemetry
• Design and implement low-latency, resource-efficient inference pipelines for on-device and edge-constrained environments
• Build simulation, replay, and regression frameworks to evaluate model performance under real-world conditions
• Analyze large-scale, real-time sensor telemetry to detect model degradation, bias, and distribution shift
• Define and track model-level metrics (accuracy, latency, power, memory) and implement monitoring and rollback strategies
• Collaborate closely with hardware, firmware, data engineering, and software teams to prototype new capabilities and ship production-quality ML systems to millions of devices worldwide

• Graduate degree in Computer Science, Data Science, or equivalent experience.
• 5 years of experience with ML training frameworks (e.g., PyTorch, Tensor Flow) and model evaluation methodologies
• 5 years of experience designing and deploying machine-learning models in production systems
• 3 years of experience handling noisy, heterogeneous, crowdsourced sensor data
• 3 years of experience designing and deploying ML models on resource-constrained devices

• Experience with real-time and/or large-scale data processing tooling (e.g. Kafka, Flink, Spark, etc.)
• Experience with sensor networks, IoT systems, or mobile sensing
• Experience with inertial sensing, time series analysis, signal processing, system identification
• Experience with multi-sensor fusion (accelerometer, gyroscope, barometer, GNSS)
• Experience monitoring ML systems in production, including drift detection, regression analysis, and iterative retraining

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $147,400 and $272,100, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including:
Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note:

Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

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.