About Us
We are a robotics startup developing advanced coordination methods that allow diverse teams of robots to work together on complex missions in real-world environments. Our focus is on building scalable optimization and planning frameworks that connect rigorous theory with practical deployment.
Role Overview
We are seeking a Research Scientist / Optimization Specialist – Multi-Agent Robotics with expertise in optimization, scheduling, and planning, and a strong interest in applying these methods to robotics. In this role, you will design and implement algorithms that tackle large-scale scheduling and task allocation problems, ensuring teams of heterogeneous robots can operate collaboratively and efficiently in dynamic environments.
Key Responsibilities
- Develop algorithms for multi-robot task allocation, scheduling, and routing.
- Apply classical optimization methods (MIP, CP, LP) to real-world robotic challenges.
- Implement and integrate solvers, including Gurobi, CPLEX, OR-Tools, and Pyomo.
- Model heterogeneous agents with varying skills, resources, and constraints.
- Research and apply approaches such as the Hungarian algorithm, auctions, and column generation.
- Build or adapt simulation tools and digital twins to generate synthetic mission/task data.
- Collaborate closely with roboticists to bring optimization frameworks into live robot deployments.
Requirements
- Ph.D. in Computer Science, Electrical Engineering, Applied Mathematics, Industrial Engineering (OR background), or a related field.
- Strong foundation in mathematical optimization and operations research.
- Hands-on experience with scheduling, assignment, or vehicle routing (VRP) problems.
- Familiarity with multi-agent systems or robotics planning.
- Proficiency in Python for optimization modeling and solver integration; some C++ experience is a plus.
- Ability to design simulations and rigorously evaluate solutions.
- Strong track record of applied research or publications in optimization, robotics, or related fields.
Nice to Have
- Background in multi-robot path finding (MAPF) or task allocation.
- Experience with simulation platforms (Isaac Sim, Gazebo, Unity).
- Exposure to mobile robot platforms (wheeled, legged, aerial).
- Experience with multi-agent RL or AI/ML approaches
Why Join Us?
- Work on real-world optimization challenges that directly impact robotics.
- Collaborate with a multidisciplinary team of high-performing researchers and engineers.
- Contribute to shaping how autonomous robots work together across industries.
- Join a group of experts with years of successful robot deployment experience.
