Machine Learning Engineer – Gurobi Scheduling Optimization; Hybrid

Overview

Machine Learning Engineer – Scheduling Optimization (Greenfield Project)

SPONSORSHIP NOT AVAILABLE- MUST BE US CITIZEN/ GREEN CARD HOLDER

LOCATION: Irvine, CA (onsite). Monday through Thursday onsite, Fridays remote.

COMPENSATION: $75-95 an hour. This is a 2-year contract that will convert to full-time.

We’re looking for our first-ever AI/ML Engineer to take full ownership of a brand-new AI scheduling engine — built entirely from the ground up. This engine will intelligently optimize scheduling for over 1 million employees worldwide, making this one of the most impactful greenfield AI initiatives you’ll find anywhere.

This is a rare opportunity to shape architecture, design, and engineering direction from day one — with complete autonomy. If you’ve ever wanted to own something end-to-end, influence technical decisions at every layer, and build a platform that will redefine workforce optimization at scale — this is it.

• Build the Core Optimization Engine: Design and implement robust optimization models using Gurobi, CPLEX, OR-Tools, or similar solvers.
• Model Real-World Complexity: Translate intricate scheduling rules — labor laws, coverage, shift constraints — into elegant, scalable mathematical formulations.
• Integrate AI & Forecasting: Combine machine learning predictions with optimization models to create smarter, adaptive scheduling recommendations.
• Engineer for Scale: Develop modular, production-grade systems in Python, with SQL and AWS for large-scale data processing and deployment.
• Collaborate & Innovate: Work with a cross-functional, startup-minded team to continuously refine models, improve performance, and push the boundaries of AI scheduling.

• Languages: Python (Pyomo, Pandas, Num Py), SQL
• Optimization Tools: Gurobi
• ML Integration: Demand forecasting, staffing prediction, and scheduling recommendations

• Hands-on experience designing and implementing optimization or constraint-based systems using Gurobi or similar tools
• Strong proficiency in Python and SQL
• Background in machine learning, forecasting, or hybrid optimization approaches
• Solid understanding of algorithms, operations research, or scheduling constraints
• Familiarity with CI/CD, Docker, and cloud deployments (AWS)

• Experience in workforce scheduling or resource optimization at scale
• Bachelor’s or Master’s in Computer Science, Operations Research, or Applied Mathematics

• 🚀 Greenfield Autonomy: Own the architecture, design, and build — no legacy code, no constraints.
• 🌍 Massive Impact: Your work will directly influence scheduling for hundreds of thousands of employees globally.
• 🧠 Cutting-Edge Tech: Blend optimization, ML, and systems design to solve complex real-world problems.
• 💡 Visionary Team: Join a team that values innovation, curiosity, and the courage to build something new from scratch.