Battery ML Engineer: Real-Time MPC & Embedded AI

Apple Inc.

California

On-site

USD 150,000 - 225,000

Full time

4 days ago

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Benefits offered by this job

Comprehensive medical and dental cover

Retirement benefits

Employee stock purchase plan (ESPP)

Discounts on products

Tuition reimbursement

Job summary

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,

Qualifications

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

Responsibilities

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.