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Python: Development skills with experience implementing, modifying, and troubleshooting production-grade ML or mathematical optimization solutions.
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Optimization / Solvers: Hands-on optimization and solver experience.
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Machine Learning: Experience working with machine learning platforms.
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Experience tuning, retraining, or reconfiguring optimization/ML solutions for different operational constraints.
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Ability to work independently in an existing codebase where documentation and subject-matter knowledge may be limited.
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Reverse-engineer and understand an existing optimization model/solver created by another team.
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Modify and customize the existing solution for different operational constraints.
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Adapt the Australian implementation to North American plant scheduling and paint/coating line requirements.
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Implement, modify, and troubleshoot production-grade ML or mathematical optimization solutions.
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Tune, retrain, or reconfigure optimization and ML solutions based on changing operational requirements.
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Support a manufacturing scheduling solution designed to minimize production transitions, machine downtime, and changeovers while maximizing throughput.
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Work independently within an existing codebase where documentation and subject-matter knowledge may be limited.
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Azure Machine Learning experience. Azure ML is desirable but should not be an absolute screening requirement if the candidate has strong ML/optimization fundamentals.
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Experience with manufacturing scheduling, production optimization, constraint optimization, or supply-chain scheduling.
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Experience working with sequencing problems involving manufacturing jobs, machine downtime, production changeovers, or similar operational constraints.
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Contrato a largo plazo.
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100% Remoto.
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Vacaciones y PTOs
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Posibilidad de recibir 2 bonos al año.
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2 revisiones salariales al año.
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Clases de inglés.
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Equipamiento Apple.
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Plataforma de cursos en linea
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Budget para compra de libros.
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Budget para compra de materiales de trabajo
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mucho mas..
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