Machine Learning Engineer, Sensing & Connectivity

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $184,700–$324,800 / yr
Posted: 1 day ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $223k

This role $255k

$161k most similar roles pay here $342k

This role pays more than 85% of similar roles. Most pay $190,750–$254,750 — the shaded band above. At the midpoint, this role pays about $255k versus about $223k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1961 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1589 roles with salary data.

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At a glance

TL;DR · Machine Learning Engineer, Sensing & Connectivity

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As a Machine Learning Engineer - Sensing & Connectivity, you will join the Applied Sensing & Health team to develop state of the art multimodal fusion of sensors and shape the intelligence of upcoming products. Your daily responsibilities include scoping, designing, and implementing models for health and fitness algorithms while validating these systems using synthetic data flows and real datasets with generative AI. You will collaborate closely with multi-disciplinary teams including scientists, engineers, QA, and project managers to deliver secure and scalable systems. The role requires expertise in machine learning and deep learning models, specifically with time series data. You will utilize Python and frameworks such as PyTorch or TensorFlow to solve complex problems involving human motion tracking and ambient sensing. Your work directly addresses the technical challenge of providing interpretable insights from sensor fusion for fitness features.

What does a Machine Learning Engineer earn in California?

Median $246150 from 173 postings across 30 companies.

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Skills

Machine Learning Deep Learning Python PyTorch TensorFlow Generative AI Statistics Data Science Sensor Fusion Scalable Systems

What you'll do

Scope, design, and implement machine learning models for health and fitness algorithms.
Develop multimodal fusion of sensors to track human motion and provide interpretable insights.
Validate algorithms using synthetic data flows and real datasets with generative AI.
Build secure and scalable systems for features on Apple Watch and iPhone.
Apply statistical approaches to data to form and prove hypotheses.
Manage the computational and storage complexities associated with modeling large datasets.
Utilize distributed compute and storage models when processing high-scale data.
Maintain the integrity of tooling and pipelines to ensure high-quality analysis.

What we're looking for

MS degree and 3+ years of experience in a quantitative data science discipline such as statistics, biostatistics, epidemiology, or computer science.
Strong background in developing machine learning and/or deep learning models, preferably with time series data.
Strong proficiency in Python and ML frameworks like PyTorch or TensorFlow.
Ph.D or 5+ years of experience in a quantitative data science discipline (preferred).
Ability to form hypotheses and creatively apply different statistical approaches to prove them (preferred).
Understanding of computational and storage complexities when modeling large datasets (preferred).
Experience leveraging distributed compute/storage models for large-scale data (preferred).
Commitment to the integrity of tooling, pipelines, and disciplined validation (preferred).