Senior Algorithm Optimization Engineer – AMR Fleet Scheduling & Traffic
Location: Tagus Park Portugal
Work Model: Hybrid 3 days on-site
Contract: Full-time
Salary: 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 Youll 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
LinkedIn:
Employment Type : Full Time
Experience: years
Vacancy: 1