Brief Summary:
Join a dynamic team as a Robotics Software Engineer, focusing on advanced fleet management algorithms to enhance efficiency and scalability in robotic systems. This role offers the opportunity to develop innovative solutions in a cutting-edge environment.
Responsibilities:
Design and develop algorithms for robotic fleet management, including task assignment, scheduling, routing, and resource allocation.
Build and maintain simulation and testing environments to evaluate fleet strategies and validate system performance.
Develop strategies to improve multi-robot coordination, traffic management, and mission dispatching in dynamic operational environments.
Analyze robot telemetry and operational data to identify system bottlenecks and drive continuous improvement.
Collaborate with cross-functional teams to ensure the reliable deployment, integration, and operational performance of fleet management solutions.
Document system designs and stay up to date with advancements in robotics, multi-agent systems, and logistics optimization.
Develop scalable software components and services that integrate with robotic systems using modern communication frameworks.
Requirements:
Master’s or Ph.D. degree in Computer Science, Robotics, Operations Research, Electrical Engineering, or a related field, with experience in robotics, optimization, or large-scale distributed systems.
Strong background in algorithms, optimization, and operations research, including scheduling, routing, and graph-based methods.
Proficiency in Python, C++, or C#, with experience developing scalable and maintainable software systems.
Experience developing algorithms for multi-agent systems, path planning, robotic coordination, and task allocation.
Familiarity with real-time systems, control theory, and optimization methods.
Strong data analysis skills, including analyzing robot telemetry, operational logs, and system performance metrics.
Experience working with robotic fleets or large-scale logistics and automation systems, including simulation and operational experimentation.
Proven ability to translate research or algorithmic innovation into practical production systems; publications or research contributions are a plus.
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