Battery Machine Learning Algorithm Engineer

Apple Inc.; California; Presencial; USD 150 000 - 225 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Comprehensive medical and dental cover

Retirement benefits

Employee stock purchase plan (ESPP)

Discounts on products

Tuition reimbursement

Resumo da oferta

Apple Inc. is seeking a Battery Machine Learning Algorithm Engineer in Cupertino, California to develop novel ML algorithms for battery systems, targeting SOH/SOP/SOC estimation and robust on‑device implementations.

The role emphasizes physics‑informed ML, adaptive control, and real‑time optimization on resource‑constrained hardware. You will collaborate with system teams, design MPC and learning‑based control frameworks, and deploy optimized models with quantization and fixed‑point arithmetic,

Qualificações

• Experience in machine learning (RNNs, LSTMs, Transformers)
• Experience in MATLAB/Simulink

Responsabilidades

• Develop ML and adaptation algorithms for SOH, SOP, SOC estimation across temperature, aging and dynamic loads.
• Build ML‑enhanced predictive models for power demand and electro‑thermal dynamics.
• Design MPC, adaptive and learning‑based control algorithms for real-time battery management and power delivery.
• Collaborate with system teams to co‑optimize battery algorithms with device power management and thermal systems.
• Develop physics‑informed ML approaches combining physics‑based models with data‑driven methods.
• Deploy algorithms on embedded platforms using model compression and fixed‑point arithmetic.

Conhecimentos

Machine learning

RNNs

LSTMs

Transformers

Control theory

Optimization

Physics-informed ML

C/C++ for embedded

Python & ML frameworks

Formação académica

PhD in a relevant field

Ferramentas

MATLAB/Simulink

PyTorch

TensorFlow

Descrição da oferta de emprego

Battery Machine Learning Algorithm Engineer

Cupertino, California, United States Hardware

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.

Responsibilities

• Develop ML and adaptation algorithms for State of Health, State of Power, and State of Charge (SOH/SOP/SOC) estimation — characterizing degradation mechanisms (capacity fade, impedance growth) and peak power capability, with robustness across temperature, cell aging, dynamic loads, and inaccurate current sensing.
• Build ML‑enhanced predictive models of user load patterns, system power demand, and coupled electro‑thermal dynamics, enabling proactive, thermal‑aware battery algorithms that extend runtime and improve power efficiency.
• Design advanced control algorithms (MPC, adaptive, learning‑based) and multi‑objective optimization frameworks to optimize battery management and power delivery in real time — balancing runtime, cycle life, thermal and system constraints, and safety margins.
• Collaborate with system teams to co‑optimize battery algorithms with device power management and thermal systems.
• Develop physics‑informed ML approaches that combine physics‑based models with data‑driven methods to improve generalization and ensure physically plausible predictions.
• Deploy algorithms on resource‑constrained embedded platforms using model compression (quantization, pruning, distillation) and fixed‑point arithmetic, with graceful fallback under sensor noise, missing data, and distribution shift.

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

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 $150,400 and $225,300, 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:

• 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.
• Comprehensive medical and dental coverage
• retirement benefits
• a range of discounted products and free services
• for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition.
• discretionary bonuses or commission payments as well as relocation.

Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation.
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

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.
Learn about accessibility in Apple’s workplace
Learn about reasonable accommodations for job applicants

Apple accepts applications to this posting on an ongoing basis.