Design of a Reinforcement Learning–Driven Scheduler for Efficient and Frugal Container Orchestr[...]

il y a 2 jours


Saclay, France CEA Temps plein

Design of a Reinforcement Learning–Driven Scheduler for Efficient and Frugal Container Orchestration H/F Position title: Design of a Reinforcement Learning–Driven Scheduler for Efficient and Frugal Container Orchestration H/F Category: Engineering science Contract type: Internship (6 months) Location: Saclay, Palaiseau, France, Île-de-France Objective: The goal of this internship is to design and evaluate a new intelligent scheduling strategy using reinforcement learning (RL), optimizing container placement, resource allocation, response time, energy consumption, and inter-container dependencies. Responsibilities 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. Qualifications Final year of a Master’s or Engineering program in Computer Science, Artificial Intelligence, or a related field. Good programming skills (Python preferred). Interest in machine learning and distributed systems. Curiosity, creativity, and strong problem‑solving abilities. Candidate criteria: Bac+5 - Diplôme École d'ingénieurs #J-18808-Ljbffr



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