Python ML & Optimization Engineer
- Python: Development skills with experience implementing, modifying, and troubleshooting production-grade ML or mathematical optimization solutions.
- Optimization / Solvers: Hands-on optimization and solver experience.
- Machine Learning: Experience working with machine learning platforms.
- Experience tuning, retraining, or reconfiguring optimization/ML solutions for different operational constraints.
- Ability to work independently in an existing codebase where documentation and subject-matter knowledge may be limited.
- Reverse-engineer and understand an existing optimization model/solver created by another team.
- Modify and customize the existing solution for different operational constraints.
- Adapt the Australian implementation to North American plant scheduling and paint/coating line requirements.
- Implement, modify, and troubleshoot production-grade ML or mathematical optimization solutions.
- Tune, retrain, or reconfigure optimization and ML solutions based on changing operational requirements.
- Support a manufacturing scheduling solution designed to minimize production transitions, machine downtime, and changeovers while maximizing throughput.
- Work independently within an existing codebase where documentation and subject-matter knowledge may be limited.
- Azure Machine Learning experience. Azure ML is desirable but should not be an absolute screening requirement if the candidate has strong ML/optimization fundamentals.
- Experience with manufacturing scheduling, production optimization, constraint optimization, or supply-chain scheduling.
- Experience working with sequencing problems involving manufacturing jobs, machine downtime, production changeovers, or similar operational constraints.
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