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Senior Algorithm Optimization Engineer – AMR Fleet Scheduling & Traffic

Velenosi&Meredith


Job Location:

Lisbon - Portugal

Monthly Salary: Not provided by the employer
Posted: 9 August 2026 (30+ days ago)
Application Deadline: 6 November 2026
Vacancies: 1 Vacancy

Job Summary

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

Send your updated CV to:

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