Remote AI Research Engineer: Agentic RL & Multimodal

Jobgether; France; A distancia; EUR 90.000 - 120.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Fully Remote

International Collaboration

Cutting-edge AI Research

Research and Innovation

Scientific Recognition

Professional Growth

Global Technology Environment

Descripción de la vacante

Jobgether is seeking an AI Research Engineer (Agentic Reinforcement Learning) based in France to push forward multimodal RL research. You will design scalable training systems and explore diffusion-based and autoregressive approaches for vision and multimodal tasks.

This fully remote opportunity enables global collaboration, top-conference publications, and translating research into real-world AI solutions across data modalities.

Formación

• Master's degree in Computer Science or a related discipline; PhD preferred.
• Strong track record of AI research with publications at major conferences.
• Experience running large-scale reinforcement learning experiments in multimodal/vision-centric systems.

Responsabilidades

• Research and develop reinforcement learning algorithms for multimodal models.
• Design scalable RL infrastructure for distributed training.
• Develop reward modeling strategies to improve training stability and alignment.
• Create multimodal simulation environments and training datasets.
• Design rigorous evaluation protocols and monitor progress against baselines.
• Analyze and optimize policy performance across modalities.
• Investigate emerging RL paradigms for better learning.
• Improve exploration, decision-making and adaptability of agents.
• Publish findings at leading conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV.

Conocimientos

Reinforcement learning

Research publications

Analytical thinking

Multimodal AI

Educación

Master's degree in Computer Science or related field

PhD preferred in ML/ML/NLP/CV

Herramientas

PyTorch

Descripción del empleo

Jobgether is seeking an AI Research Engineer (Agentic Reinforcement Learning) based in France to push forward multimodal RL research. You will design scalable training systems and explore diffusion-based and autoregressive approaches for vision and multimodal tasks.

This fully remote opportunity enables global collaboration, top-conference publications, and translating research into real-world AI solutions across data modalities.