Industrial ML Engineer: Optimization & Digital Twin

Apple Inc.

Cupertino, Northern (CA, KY)

Hybrid

USD 150,000 - 278,000

Full time

7 days ago

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Benefits offered by this job

Medical coverage

Employee stock programs

Relocation assistance

Tuition reimbursement

Job summary

Apple Inc. is seeking a machine learning/operations research engineer in Cupertino to apply advanced mathematical modeling, statistical analysis, and optimization to solve complex manufacturing challenges.

You will influence factory throughput, supply chain strategies, and cost-reduction efforts by turning data into decisions. The role emphasizes production optimization, simulation, and data fusion, with collaboration across engineering, operations, and product teams.

Qualifications

Master’s degree or PhD in Operations Research, Industrial Engineering, Management Science, Applied Mathematics, or related field.
Proficiency with solvers and modeling languages such as Gurobi, CPLEX, CP-SAT, Pyomo, and GAMS.
Hands‑on experience with simulation platforms like Arena, FlexSim, SimPy, and AnyLogic.
Experience with machine learning platforms such as PyTorch and Scikit‑learn.
Excellent communication and presentation skills; ability to explain complex statistical and mathematical theories to non‑technical stakeholders in simple, universal language.

Responsibilities

Production Optimization: Develop and implement mathematical models for optimization of capacity, yield, cycle times, costs, throughput, shop-floor layout usage, dynamic scheduling, and other factory and supply chain metrics.
Simulation Modeling: Build and maintain mathematical models for simulation to act as a "digital twin" of our assembly lines, identifying bottlenecks and testing "what-if" capacity scenarios.
Data fusion and analytics: Develop and implement data fusion techniques to integrate different operational data sources and generate actionable insights for manufacturing intelligence.