468 jobs for "Assembly I"

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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.","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.

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.

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.

Pay & Benefits

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 $277,600, 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: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

About Apple

Working at Apple means doing more than you ever thought possible and having more impact than you ever imagined.

Size: 10,000+ employees
Industry: Technology: Manufacturing

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