About the job
Join Hadrian , Pioneering the Future of Manufacturing
At Hadrian, we're at the forefront of revolutionizing manufacturing for the aerospace and defense sectors. Our autonomous factories empower companies to produce rockets, satellites, jets, and ships at speeds up to 10 times faster and costs slashed by half. By integrating state-of-the-art software, robotics, and comprehensive manufacturing processes, we are redefining how critical parts are made in America.
With a recent $260 million Series C funding round, we're expanding our vision. Our new state-of-the-art facility in Mesa, Arizona, spans 270,000 square feet and will create 350 immediate job opportunities. As we establish our headquarters to support thousands of future roles, we're also launching Hadrian Maritime for naval production and introducing a Factory-as-a-Service model for delivering complete systems.
Our partnerships range from startups to Tier 1 and Tier 2 suppliers, and major defense contractors across space, shipbuilding, and aviation. We are dedicated to scaling production, minimizing costs, and accelerating deliveries for mission-critical programs. Backed by prestigious investors like Lux Capital, Founders Fund, and Andreessen Horowitz, our rapidly growing team is committed to reindustrializing American manufacturing for the 21st century and beyond!
Your Role
As the Operations Research Scientist at Hadrian, you will spearhead initiatives to enhance manufacturing efficiency through advanced optimization techniques. You will confront intricate challenges in scheduling, capacity planning, and resource allocation within aerospace manufacturing. Utilizing cutting-edge solvers and potentially Reinforcement Learning methodologies, you will develop systems that optimize everything from production queues to tool utilization. Your innovative algorithms will directly influence delivery times, cost reductions, and the scalability of our manufacturing operations.
Key Responsibilities
Design and deploy advanced production scheduling algorithms utilizing CP-SAT and MIP solvers.
Construct capacity planning models that effectively balance demand with resource limitations.
Develop queue management systems aimed at optimizing throughput and minimizing wait times.
Create demand forecasting models employing modern time series methodologies.
Optimize inventory levels for raw materials and work-in-progress items.
Design innovative tool allocation algorithms that consider utilization rates and maintenance schedules.
Implement robust optimization strategies to address uncertain demand and processing durations.
Collaborate with cross-functional teams to ensure successful project implementation and continuous improvement.
