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Salary
≈ $223k – $420k per year (Estimated)
Location
In office (Cupertino)
Seniority
Middle · 3+ years exp
Visa
H-1B filings in 12 months: 6,350 · for this role: 2,959 · green card filings: 37

Confirmed on the employer's own hiring board on Oct 17, 2026. First seen by Alion on Oct 16, 2026. Apple scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Apple is an American multinational technology company founded in 1976 by Steve Jobs, Steve Wozniak and Ronald Wayne, and headquartered in Cupertino, California. It designs and sells consumer hardware including the iPhone, Mac, iPad, Apple Watch, AirPods and Vision Pro, together with the operating systems and silicon that run them. A growing services division built around the App Store, iCloud, Apple Music, Apple TV+ and Apple Pay now contributes a large share of profit, making Apple one of the most valuable companies in the world.

Join Apple's HID sensing and interaction algorithms team, which develops advanced sensing algorithms that enable best-in-class user experiences across Mac, iPhone, iPad, Apple Pencil, Apple Watch, and exciting new products. We are looking for a machine learning engineer with hands-on generative AI experience and a strong foundation in signal processing, who is excited to apply both to how people interact with Apple products.

Our team draws from diverse backgrounds: signal processing, machine learning, firmware, software engineering, physics, human factors, and more; all dedicated to inventing new ways users interact with Apple products. You will work at the intersection of hardware, software, and design, collaborating with specialists across Apple to ship extraordinary products to millions of users every year.

Description

In this role, you will help explore how generative AI can advance sensing and interaction. You will research, develop, and evaluate generative models and AI systems for physical signals such as time series and images. Success here is measured by real-world impact on products and users, not by leaderboard numbers. That takes a deep understanding of the signals you model and statistical rigor in how you judge results. These are challenging, open-ended problems, and we are looking for someone with the persistence to carry an idea all the way into production.

You will also bring a solid understanding of physical signals and signal processing, and use it to develop sensing algorithms for products. You will collaborate with algorithm, firmware, and software engineers to deliver features from prototyping through production.

We value engineers who check their claims against real data, report negative results honestly, and explain technical findings clearly to people outside their field.

Minimum Qualifications

BS in Computer Science, Electrical Engineering, or a related STEM field with a minimum of 3 years of relevant industry or research experience

Hands-on experience developing generative AI models or systems that go beyond tutorials, such as through shipped products, publications, or substantial projects

Experience working with real-world sensor or physical measurement data. Strong understanding of physical signals such as time series and images, and how their structure and noise shape what a model learns

Solid foundation in digital signal processing and time-series analysis, such as filtering, spectral analysis, and feature extraction

Strong Python programming skills and proficiency with a modern deep learning framework such as PyTorch

Preferred Qualifications

MS or PhD in machine learning, signal processing, electrical engineering, physics, or a related field, with publications, open-source contributions, or shipped products in generative AI

Experience training generative or other ML models on time-series, sensor, audio, or image data, including at scale on GPU clusters

Statistical rigor in designing experiments and evaluations and in interpreting their results, backed by reproducible research practices

Experience using LLM-based AI assistants and agents to accelerate research and development work, such as coding, data analysis, and experiment automation

Proficiency in C/C++, and familiarity with embedded or resource-constrained systems

Demonstrated persistence in driving a challenging project from idea to production or real-world deployment

Excellent communication and cross-functional collaboration skills across algorithms, firmware, and software disciplines

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