Battery Machine Learning Algorithm Engineer

Apple • Operating Systems • Laptops • Doctoral Degree (PhD) • Python • C++ • MATLAB • 8 hours ago
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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 16, 2026. First seen by Alion on Oct 16, 2026. Apple scores B on the Alion truth index.

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Apple

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.
apple.com • HQ: Cupertino, United States • Smartwatches & Fitness Trackers • Operating Systems • Tablets • Laptops • Smartphones • 5000+ employees • Est. 1976
Tech stack of Apple

Envision what you could do here. At Apple, we believe new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.

Description

We are looking for an engineer who will develop novel machine learning algorithms, control strategies, and on-device implementations to improve the utility and intelligence of battery systems.

Minimum Qualifications

Experience in machine learning (RNNs, LSTMs, Transformers), control theory and optimization (MPC, Kalman filters, convex/nonconvex optimization)

Experience in MATLAB/Simulink

Preferred Qualifications

PhD and 3+ years relevant industry experience

Mathematical modeling experience for nonlinear dynamical systems

Experience in C/C++ for embedded systems and Python & ML frameworks (PyTorch, TensorFlow)

Experience with physics-informed neural networks or hybrid physics/ML approaches

Experience with MPC implementation and real-time optimization

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