Research Scientist​/Optimization Specialist – Multi-Agent Robotics

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.

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.

• 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.

• 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.

• 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

• 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.