Senior Algorithm / Optimization Engineer - AMR Fleet Scheduling & Traffic
Velenosi&Meredith
Location: Tagus Park, Portugal
Work Model: Hybrid – 3 days on-site
Contract: Full-time
Salary: €60,000–€80,000 gross/year × 14 salaries
Relocation: No relocation support provided
About the Role
We are looking for a Senior Algorithm / Optimization Engineer to design and implement advanced algorithms for Autonomous Mobile Robot (AMR) fleet scheduling, routing, order assignment, and traffic optimization .
This is a hands-on engineering role combining mathematical optimization, logistics planning, and production-grade software development .
What You'll Do
- Design algorithms for AMR assignment, scheduling, routing, and fleet optimization
- Model orders, priorities, deadlines, routes, robot capabilities, and operational constraints
- Develop fast, executable planning solutions balancing optimality and real-time performance
- Work with historical and live data to improve travel-time estimates and planning quality
- Build simulation, benchmarking, and validation tools
- Integrate algorithms into production backend and fleet-management systems
- Collaborate with Backend, Robotics, Product, QA, Simulation, and Fleet Management teams
Requirements
- Strong background in mathematical optimization, algorithms, Operations Research, or applied mathematics
- Experience with combinatorial optimization, scheduling, routing, assignment, or resource allocation
- Strong programming skills in Rust and/or Python
- Production software engineering experience — not only research or prototypes
- Understanding of algorithms, constraints, objective functions, heuristics, and runtime complexity
- Experience with APIs, backend services, testing, Git, CI/CD, and performance optimization
- Ability to evaluate algorithms using simulation, benchmarks, data, and operational KPIs
- Understanding of logistics, fleet planning, or complex scheduling problems
Nice to Have
- AMR/AGV, robotics, warehouse automation, or intralogistics experience
- OR-Tools, MILP, CP-SAT, constraint programming, or similar
- Vehicle routing, job-shop scheduling, pathfinding, or traffic management
- Machine learning/statistical modelling applied to operational problems
- Docker/Kubernetes
- ROS, VDA 5050, MQTT, Kafka, Redis, or similar technologies
- Simulation/digital twin experience
Important
This is not a pure Data Science or theoretical research role .
Candidates must be able to translate mathematical and optimization concepts into robust, maintainable, production-ready algorithms used in real-world fleet operations.
Interested?
Send your updated CV to: Mostrar e-mail
LinkedIn:
Vaga publicada 2 meses atrás
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