Network Optimization & AI/ML Engineer, IRIS2

SES Satellites; Unterföhring; Hybrid; EUR 90.000 - 130.000; Vollzeit

Zusammenfassung

SES Satellites seeks a Network Optimization & AI/ML Engineer to develop optimization models, algorithms, and data-driven techniques for routing, traffic engineering, capacity allocation, prediction, and autonomous network behavior in a multi-orbit satellite environment.

The role sits at the intersection of operations research, graph algorithms, machine learning, AI-driven decision support, and network engineering, translating complex constraints into practical algorithms that improve latency,

Qualifikationen

• Advanced degree in Computer Science, Electrical Engineering, Applied Mathematics, Operations Research, Data Science, or related field.
• Strong foundation in optimization, including convex optimization, linear programming, integer programming, combinatorial optimization, heuristics, and metaheuristics.
• Strong foundation in graph theory, network flow, routing algorithms, stochastic processes, queueing theory, and performance modeling.
• Hands-on experience with machine learning, time-series forecasting, anomaly detection, reinforcement learning, or AI-driven decision systems.
• Programming skills in Python and tools such as NumPy, SciPy, PyTorch, TensorFlow, OR-Tools, Gurobi, CPLEX, or similar frameworks.
• Ability to design statistically rigorous experiments, evaluate algorithm performance, and communicate assumptions clearly.
• Familiarity with SDN, traffic engineering, satellite networks, telecom systems, or distributed network control.
• Experience moving research prototypes toward maintainable software components or operational decision-support tools.

Aufgaben

• Formulate optimization problems for routing path selection, traffic engineering, resource allocation, congestion mitigation, and service assurance.
• Develop algorithms for dynamic, multi-layer satellite-terrestrial network scenarios with changing topology, demand, failures, and constraints.
• Apply AI/ML techniques for traffic prediction, anomaly detection, failure mitigation, self-optimization, and decision support.
• Build prototypes and evaluation pipelines to compare optimization strategies against baseline routing and control-plane approaches.
• Collaborate with architecture, simulation, control-plane, software, and validation teams to integrate algorithms into workflows.
• Define objective functions, constraints, metrics, data requirements, and validation approaches for algorithmic network optimization.
• Analyze trade-offs across latency, throughput, availability, fairness, capacity, security, and operational complexity.
• Document mathematical models, assumptions, performance results, and implementation guidance for stakeholders.

Kenntnisse

Optimization

Graph theory

Machine learning

Python

Operations research

Time-series forecasting

Reinforcement learning

Ausbildung

Advanced degree in CS/EE/OR/DS

Related field or equivalent experience

Tools

NumPy

SciPy

PyTorch

TensorFlow

OR-Tools

Gurobi

CPLEX

Jobbeschreibung

(Senior) Engineer, Network Optimization & AI/ML, IRIS2

The job responsibilities outlined in this document are not exhaustive and may evolve over time and be reviewed according to business needs.

Programme Description

IRIS2 is the new European Union secure satellite constellation. This project is the European Union's answer to the pressing challenges of tomorrow to provide secure connectivity services and enhanced communication capacities to the EU and its Member States. In addition, as well as to governmental users, private companies and European citizens while benefiting from ensuring high-speed internet broadband to cope with connectivity dead zones.

Requisition Number: 20224

Contract Type: Permanent

Location(s): Betzdorf, LU Munich (Unterföhring), DE

SES – together with other consortium partners and core members, was selected by the European Commission to build and to operate the IRIS2 multi-orbit satellite constellation.

The IRIS2 team enters next project phases, we seek and there is a strong need of support for all the activities around service provisioning and products that the system can offer in the future.

Role Description Summary

We are seeking a Network Optimization & AI/ML Engineer to develop optimization models, algorithms, and data-driven techniques for routing path selection, traffic engineering, capacity allocation, prediction, and autonomous network behavior in a multi-orbit satellite communications environment. This role sits at the intersection of operations research, graph algorithms, machine learning, AI-driven decision support, and network engineering. The position is ideal for someone who can transform complex network and constellation constraints into practical algorithms that improve latency, capacity utilization, resilience, and operational efficiency.

Primary Responsibilities / Key Result Areas

• Formulate optimization problems for routing path selection, traffic engineering, resource allocation, congestion mitigation, and service assurance.
• Develop algorithms for dynamic, multi-layer satellite-terrestrial network scenarios with changing topology, demand, failures, and operational constraints.
• Apply AI and machine learning techniques for traffic prediction, anomaly detection, failure mitigation, self-optimization, and decision support.
• Build prototypes and evaluation pipelines to compare optimization strategies against baseline routing and control-plane approaches.
• Work with architecture, simulation, control-plane, software, and validation teams to integrate algorithms into experimental and production-oriented workflows.
• Define objective functions, constraints, metrics, data requirements, and validation approaches for algorithmic network optimization.
• Analyze trade-offs across latency, throughput, availability, fairness, capacity, security, and operational complexity.
• Document mathematical models, assumptions, performance results, and implementation guidance for technical and programme stakeholders.

Qualifications Background And Experience

• Advanced degree in Computer Science, Electrical Engineering, Applied Mathematics, Operations Research, Data Science, or a related field, or equivalent professional experience.
• Strong foundation in optimization, including convex optimization, linear programming, integer programming, combinatorial optimization, heuristics, and metaheuristics.
• Strong foundation in graph theory, network flow, routing algorithms, stochastic processes, queueing theory, and performance modeling.
• Hands-on experience with machine learning, time-series forecasting, anomaly detection, reinforcement learning, or AI-driven decision systems.
• Programming skills in Python and experience with scientific computing and optimization tooling such as NumPy, SciPy, PyTorch, TensorFlow, OR-Tools, Gurobi, CPLEX, or similar frameworks.
• Ability to design statistically rigorous experiments, evaluate algorithm performance, and communicate assumptions and limitations clearly.
• Familiarity with SDN, traffic engineering, satellite networks, telecom systems, or distributed network control is highly valuable.
• Experience moving research prototypes toward maintainable software components or operational decision-support tools.

Other Key Requirements / Comments

• The candidate must be eligible for a “SECRET” security clearance, in accordance with the national regulations as well as EU/ESA/NATO equivalents
• Willing to work 60% onsite from office
• Travel as required for project realization purposes

SES and its Affiliated Companies are committed to providing fair and equal employment opportunities to all. We are an Equal Opportunity employer and will consider all qualified applicants for employment without regard to race, color, religion, gender, pregnancy, sex, sexual orientation, gender identity, national origin, age, genetic information, protected veteran status, disability, or any other basis protected by local, state, or federal law.

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