Python ML & Optimization Engineer
Worldwide | Nov. 9, 2026
Report as Closed
Company:
Improving
Country: Worldwide
Type: Remote
Employment: Full-time
Description: Improving is an IT services firm focused on AI, Data, and Applications. We modernize legacy systems, build cloud-native platforms, and deliver future-ready solutions through collaborative, long-term partnerships that drive measurable outcomes.
At Improving South America, we provide IT services to transform the perception of the IT professional. We focus on IT consulting, software development and agile training.
The company promotes an exceptional work culture based on teamwork, excellence and fun, with a focus on personal growth and shared rewards. By joining, the candidate will become part of a community that prioritizes open communication and strong long-term working relationships, supported by a structure of professional development and continuous learning.
- 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.
The role focuses on reverse-engineering and adapting an existing optimization solution for manufacturing scheduling.
The engineer will take an existing model/solver created by another team, understand it, and modify/customize it rather than developing an algorithm from scratch.
The application supports a manufacturing process where the sales team gathers customer orders, with customers providing the metal and paint, sometimes on short notice. The tool is designed to minimize transition time during production. A paint change can require approximately 20 minutes, so the solution helps reduce these transitions and maximize throughput by grouping paints by color, grouping steel dimensions, and minimizing downtime on the production line.
Job functions
- 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.
Benefits
- Long-term contract.
- 100% Remote.
- Vacation and PTOs
- Possibility of receiving 2 bonuses per year.
- 2 salary reviews per year.
- English classes.
- Apple equipment.
- Online course platform
- Budget for purchase of books.
- Budget for purchasing work materials
- much more...
Nice to have skills
- 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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