Machine Learning Engineer – Scheduling Optimization (Hybrid)

Own the core optimization engine by designing robust models using Gurobi, CPLEX, OR-Tools, or equivalent solvers.
Translate complex scheduling rules—labor laws, coverage, shift constraints—into scalable mathematical formulations.
Integrate ML forecasts with optimization to deliver adaptive, data-driven scheduling recommendations.
Build modular, production-grade Python systems with SQL and AWS for large-scale data processing and deployment.
Collaborate with a cross-functional, startup-minded team to continuously refine models and push performance.
Enjoy complete autonomy over architecture, design directions, and roadmap in a greenfield project.