Machine Learning Engineer - Scheduling Optimization (Greenfield Project)
SPONSORSHIP NOT AVAILABLE- MUST BE US CITIZEN/ GREEN CARD HOLDERLOCATION: Irvine, CA (onsite). Monday throughThursday 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.