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Apple

Machine Learning Engineer

Apple Cupertino, California, United States

Computers and Electronics Manufacturing · 10,001+ employees

3 h ago
machine-learning Senior (5-10 yrs) Full-time United States
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About the role

Apply advanced mathematical modeling and optimization algorithms to solve complex manufacturing challenges. Transform raw operational data into actionable decisions to improve factory throughput and supply chain strategies.

What they look for

Machine Learning Operations Research Mathematical Modeling Statistical Analysis Optimization Algorithms Gurobi CPLEX PyTorch Scikit-learn GenAI LLM Development Kubernetes Apache Airflow Docker Ray Data Analysis

Requirements

Requires a Master’s degree or PhD in Operations Research, Industrial Engineering, or a related field. Proficiency in modeling languages, simulation platforms, and machine learning frameworks is essential.

Full description

Imagine what you could do here. At Apple, 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.

The people here at Apple don’t just create products — they create the kind of wonder that’s revolutionized entire industries. It’s the diversity of those people and their ideas that inspires the innovation that runs through everything we do, from amazing technology to industry-leading environmental efforts. Join Apple and help us leave the world better than we found it.

Description

With the explosive growth of Apple products we are creating new opportunities for individuals to work on the most exciting new technologies at Apple. We are seeking a machine learning/operations research engineer to apply advanced mathematical modeling, statistical analysis, and optimization algorithms to solve complex manufacturing challenges. Machine learning/operations research engineers on our team directly impact our factory throughput, supply chain strategies, and cost-reduction initiatives by transforming raw operational data into actionable, data-driven decisions.

Minimum 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.

Preferred Qualifications

Proven experience in GenAI application building with agents and agentic workflows. Experience with LLM and LMM development and fine-tuning is a major plus. Proficiency in using cutting-edge GenAI tools, i.e. Claude Code, Roo Code, etc. Familiarity with distributed computing, cloud infrastructure, and orchestration tools, such as Kubernetes, Apache Airflow (DAG), Docker, Conductor, Ray for LLM training and inference at scale is a plus.

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