Senior Algorithm / Optimization Engineer – AMR Fleet Scheduling & Traffic

Velenosi&Meredith; Lisboa; Presencial; EUR 60 000 - 80 000; Tempo integral

Resumo da oferta

Velenosi&Meredith is seeking a Senior Algorithm / Optimization Engineer in Tagus Park, Portugal for hybrid work. The role focuses on designing and implementing advanced optimization algorithms for AMR fleet scheduling, routing, and order assignment, balancing real-time performance with optimality in production software.

You will model orders, deadlines, routes, robot capabilities, and constraints, and build tools for simulation, benchmarking, and validation while collaborating with multiple

Qualificações

• 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 just 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.

Responsabilidades

• 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

Conhecimentos

Mathematical optimization

Algorithms

Operations Research

Applied mathematics

Combinatorial optimization

Scheduling

Routing

Assignment

Resource allocation

Rust

Python

Backend APIs

CI/CD

Performance optimization

Simulation

Ferramentas

Git

CI/CD tools

Docker

Kubernetes

ROS

Descrição da oferta de emprego

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/