AlphaZ
Research Scientist / Optimization Specialist – Multi-Agent Robotics
AlphaZ, Los Angeles, California, United States, 90079
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.
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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.
#J-18808-Ljbffr