Senior Algorithm / Optimization Engineer – AMR Fleet Scheduling & Traffic

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.

LinkedIn:

https://www.linkedin.com/in/dylan-デ-a78965140/

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