Remote Python ML & Optimization Engineer

Ulvior; United States; Remote; USD 120,000 - 160,000; Full time

Benefits offered by this job

Long-term contract

100% Remote

Vacation and PTOs

Two annual bonuses

Two salary reviews per year

English classes

Apple equipment

Online courses platform

Budget for books

Budget for work materials

Job summary

Ulvior is seeking an experienced ML/Optimization engineer to design, implement, and optimize production-grade ML and optimization solutions. You will work with Python, solvers, and scheduling challenges across manufacturing lines, including NA adaptations.

This long-term, 100% remote role offers ongoing learning opportunities, salary reviews, English classes, and access to training budgets.

Responsibilities

• Develop and maintain production-grade ML/optimization solutions in Python.
• Tune and troubleshoot models to meet production needs.
• Reverse-engineer and understand an existing optimization model/solver.
• Modify and customize the existing solution for different operational constraints.
• Adapt NA plant scheduling and line requirements from an Australian implementation.
• Implement, modify and troubleshoot production-grade ML or optimization solutions.
• Tune, retrain, or reconfigure optimization and ML solutions as requirements change.
• Support a manufacturing scheduling solution to minimize transitions, downtime and changeovers while maximizing throughput.
• Work independently within an existing codebase with limited documentation.

Skills

Python

Optimization

Machine Learning

Model Tuning

Independent Work

Reverse Engineering

Customization

Adaptation

Scheduling

Sequencing

Tools

Azure ML

Job description

Ulvior is seeking an experienced ML/Optimization engineer to design, implement, and optimize production-grade ML and optimization solutions. You will work with Python, solvers, and scheduling challenges across manufacturing lines, including NA adaptations.

This long-term, 100% remote role offers ongoing learning opportunities, salary reviews, English classes, and access to training budgets.