Warehouse Execution System and Fleet Management Team
Orchestrating warehouse execution systems, multi-agent AGV/AMR fleet traffic, and end-to-end material flow across 24/7 automated logistics facilities.
Team Overview
The Warehouse Execution System and Fleet Management team designs, builds, and scales the orchestration layer that coordinates robots, automated equipment, and autonomous mobile vehicles across modern logistics facilities.
Without WES, Mujin’s cutting-edge robots cannot fully realize their potential in the real world. WES is what brings those robots into real-world operations, enabling them to work reliably around the clock and under real-world conditions. This is how we turn Mujin’s vision into reality: “Liberate humans from manual labor to make them focus on creativity, innovation, and making the world a better place.”
Our real-world impact is keeping logistics moving, even when people can’t. By orchestrating robots efficiently, WES enables logistics operations to run around the clock with less dependence on manual labor. As the workforce shrinks while our expectations for fast and convenient logistics continue to grow, our systems support the logistics that people rely on every day.
Products & Applications Powered by This Team
Mujin WES (Warehouse Execution System)
Orchestrates high-level material flow, real-time order scheduling, dynamic buffer allocation, and multi-equipment handshakes across the entire logistics facility.
Mujin Fleet Manager
Directs AGV and AMR fleet navigation, dynamic multi-vehicle path planning, traffic deadlock prevention, and synchronized pickup/drop-off station transfers.
Tech Stack
Languages & Toolchains
- Languages: C++, Python
- Development & Packaging: Linux development environments, Docker
- Reliability & Debugging: Software debugging tools, asynchronous communication pipelines, and operational state recovery
Core Engineering
- Order Scheduling & Work Release: Application-level order scheduling, task dependency modeling, and dynamic resource allocation
- Graph Modeling & Fleet Planning: Graph modeling and scheduling methods for reasoning about routes, competing work, and AGV/AMR traffic
- Multi-Equipment Coordination: Transfer handshakes, buffer capacity tracking, and equipment readiness verification across robot cells, conveyors, and shuttles
- Performance Analysis: Performance analysis across software services, industrial equipment, and complete warehouse workflows
Hardware, Integration & Equipment
- Robotics & Material Handling: Robot cells, industrial conveyors, and PLCs
- Mobile Robotics: Automated Guided Vehicles (AGVs) and Autonomous Mobile Robots (AMRs)
- High-Density Storage: Automated Storage and Retrieval Systems (AS/RS) and pallet shuttles
- Enterprise Systems: Interfaces with external Warehouse Management Systems (WMS) and facility equipment systems
Technical Challenges
Keeping Goods Moving Efficiently Under Changing Loads
Challenge: Orders for different destinations compete for processing capacity, transport resources, and space. Releasing work too early can fill buffers with goods that cannot move forward. Releasing it too late can put dispatch deadlines at risk. The scheduler must remain responsive through quiet periods, demand spikes, and uneven equipment loads, accounting for order priorities and the current state of the operation.
Approach: Represent orders as dependent tasks and release work when the required resources and downstream capacity are available. Adjust work release and priorities as demand changes, tasks finish, or equipment becomes unavailable, preventing queues from growing beyond what downstream processes can handle. Keep each movement linked to its order and destination so that a local scheduling decision supports the complete fulfillment process.
Impact: Efficient goods processing across changing workloads, more predictable order completion, and less congestion or manual rescheduling.
Coordinating Handoffs Across Different Equipment
Challenge: A warehouse workflow crosses equipment with different interfaces, cycle times, and failure behavior. A storage system may finish a retrieval before transport is available, or a robot cell may complete work while the receiving conveyor is full. WES must coordinate these transitions and track whether each transfer actually completed, including when acknowledgments are delayed or equipment stops midway.
Approach: Model equipment availability and transfer stages explicitly, with agreed readiness and completion conditions at each interface. Sequence retrieval, transport, and processing tasks around receiving capacity. Connect AGV/AMR assignments and path planning to the readiness of pickup and drop-off stations. Extend automated execution to routine handoffs and recoverable exceptions. Reconcile task state after interruptions and resume or retry when the outcome is known and conditions permit; provide clear escalation when operator intervention is required.
Impact: More warehouse flows completed automatically, fewer manual interventions, less avoidable equipment waiting, and more predictable recovery across the complete workflow.
Key Responsibilities
- Design order scheduling and work-release logic around warehouse priorities and dispatch requirements.
- Develop and maintain driver-level support for new warehouse hardware, integrating device commands, status, and error handling into the backend and application workflows.
- Coordinate robot cells, conveyors, AS/RS, pallet shuttles, and AGVs/AMRs through equipment interfaces and explicit handoff conditions.
- Expand automated warehouse flows and recovery paths to reduce manual intervention, while adapting work release to changing demand, buffer capacity, and equipment availability.
- Develop AGV/AMR fleet management and path planning in coordination with warehouse tasks and station readiness.
- Engineer reliable execution and recovery for delayed responses, interrupted transfers, and service restarts, preserving goods and order state throughout.
- Validate complete workflows and diagnose production issues across software and physical operations.
Weekly Engineering Rhythm
- 30% Software design and implementation
- 30% Simulation and integration testing
- 40% Hands-on testing with warehouse equipment
Who Will Enjoy and Excel on This Team
If you want your code to orchestrate complex physical operations across entire logistics centers rather than remaining isolated in pure software silos, this team is an exceptional environment. You will excel and have the most fun here if you:
- Solve Complex, System-Wide Problems: You enjoy optimizing not just individual components, but how robots, AGVs/AMRs, software services, and warehouse equipment work together as a unified whole.
- Thrive Where Software Meets the Real World: You are motivated by solving problems where software meets physical constraints, hardware unpredictability, and actual robot behavior.
- Care About Real-World Production Performance: You prioritize reliability, low latency, and robustness in systems that need to operate continuously 24/7 in actual warehouse environments.
Who Might Struggle on This Team
- Engineers who prefer optimizing a single component in isolation: If your passion is solely making one isolated algorithm or component smarter rather than reasoning across multi-tier distributed systems, our cross-cutting architecture will feel overwhelming.
- Engineers who prefer purely virtual or simulated environments: If you dislike interacting with physical machinery, hardware interfaces, or hands-on testing on the warehouse floor, you will not enjoy our 40% hands-on testing rhythm.
- Engineers seeking primarily early-stage 0-to-1 business building: If you are looking for early-stage startup ideation from scratch rather than scaling mission-critical industrial production systems, this team’s focus may not align with your expectations.
Join the Team
Qualifications & Growth
- Strong Programming Proficiency: Solid software development skills in C++ and Python.
- Systems & Linux Fundamentals: Linux development, networking fundamentals, asynchronous I/O, and containerization with Docker.
- Technical Communication & Stakeholder Collaboration: Clear communication and collaboration with project managers: clarify customer requirements, explain technical tradeoffs in practical terms, and communicate progress, risks, and blockers early.
- Education & Experience: A relevant degree in Computer Science, Systems Engineering, Robotics, or equivalent practical industry experience.
- Industrial Robotics at Scale: Real-world applications of industrial robotics and the challenge of optimizing robots within real-world constraints.
- Mission-Critical Production Engineering: Learn what real-world operations actually demand by working on projects with some of Japan’s largest companies, then turn those needs into systems that are deployed and used in practice.
- Fleet & Warehouse Orchestration: Multi-agent traffic control, dynamic routing, equipment handoff modeling, and autonomous deadlock resolution.