Machine Learning/Operations Research Engineer

Apple • Cupertino, CA

4d

About The Position

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.

Requirements

• 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.

Nice To Haves

• 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.

Responsibilities

• Apply advanced mathematical modeling, statistical analysis, and optimization algorithms to solve complex manufacturing challenges.
• Directly impact factory throughput, supply chain strategies, and cost-reduction initiatives.
• Transform raw operational data into actionable, data-driven decisions.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior