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Design of a Reinforcement Learning–Driven Scheduler for Efficient and Frugal Container Orchestration H/F

Design of a Reinforcement Learning–Driven Scheduler for Efficient and Frugal Container Orchestration H/F

On site

Saclay, France

Internship

17-01-2026

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Skills

Communication Creativity Python Docker Kubernetes Resource Allocation Problem-solving Machine Learning Programming Artificial Intelligence

Job Specifications

Position description Category

Engineering science

Contract

Internship

Job title

Design of a Reinforcement Learning–Driven Scheduler for Efficient and Frugal Container Orchestration H/F

Subject

Context: Modern distributed systems (such as cloud and edge computing platforms) rely on orchestration frameworks like Kubernetes or Docker Swarm to manage the deployment and execution of applications. A key challenge in these environments is how to schedule containers efficiently, deciding which node should run each task, while balancing performance, energy efficiency, and resource usage.

Contract duration (months)

6 months

Job Description

Objective: The goal of this internship is to design and evaluate a new intelligent scheduling strategy using reinforcement learning (RL). The idea is to enable the system to learn how to make smarter scheduling decisions over time, optimizing

container placement and sizing,
dynamic resource allocation,
response time and energy consumption
and even inter-container dependencies such as shared data or communication patterns.

Your missions: During this internship, you will:

Explore and understand the orchestration framework developed within the team.
Conduct a state-of-the-art study on RL-based scheduling in cloud and distributed environments.
Design, implement, and train a new RL-based scheduler.
Develop a feature extraction module to characterize container behavior and guide the RL agent’s decisions.
Evaluate your approach through experiments and benchmark comparisons

Applicant Profile

Profile sought

We are looking for a motivated student in the final year of a Master’s or Engineering program in Computer Science, Artificial Intelligence, or a related field, with:

Good programming skills (Python preferred).
Interest in machine learning and distributed systems.
Curiosity, creativity, and strong problem-solving abilities.

Position location Site

Saclay

Job location
France, Ile-de-France

Location

Palaiseau

Candidate criteria Prepared diploma

Bac+5 - Diplôme École d'ingénieurs

About the Company

The CEA is the French Alternative Energies and Atomic Energy Commission ("Commissariat à l'énergie atomique et aux énergies alternatives"). It is a public body established in October 1945 by General de Gaulle. A leader in research, development and innovation, the CEA mission statement has two main objectives: To become the leading technological research organization in Europe and to ensure that the nuclear deterrent remains effective in the future. The CEA is active in four main areas: low-carbon energies, defense and secur... Know more