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.

About the Role

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.

What You’ll Do

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.

Tech Stack

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

What You Bring

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)

Bonus Points

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

Why This Role Is Exciting

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.

Machine Learning Engineer – Gurobi Scheduling Optimization (Hybrid)

Job Type