Fully Remote Agentic RL Research Engineer - Multimodal AI

Jobgether; Ireland; Remote; EUR 90,000 - 140,000; Full time

Benefits offered by this job

Fully Remote Work

International Collaboration

Cutting-Edge AI Research

Job summary

Jobgether is seeking an AI Research Engineer (Agentic Reinforcement Learning) based in Ireland. You will conduct advanced research and develop scalable reinforcement learning systems for multimodal AI applications, spanning text, images, audio, and beyond.

The role emphasizes state‑of‑the‑art methods, scalable infrastructure, and robust evaluation. You will publish at top conferences and contribute to globally distributed teams in a fully remote setting.

Qualifications

• Master's degree in CS or related; PhD preferred in ML/NLP/CV.
• Strong track record of AI research with conference publications.
• Experience with large-scale reinforcement learning in multimodal systems.
• Proficiency in PyTorch and modern DL frameworks.
• Experience designing end-to-end RL pipelines from simulation to deployment.
• Ability to translate research into practical AI solutions.

Responsibilities

• Research and develop RL algorithms for multimodal models.
• Design scalable RL infrastructure for distributed training.
• Develop reward modeling strategies to improve training stability.
• Create and maintain multimodal simulation environments and datasets.
• Design evaluation protocols and monitor progress against baselines.
• Analyze and optimize policy performance across modalities.
• Publish and present research at ICML, NeurIPS, ICLR, CVPR, ICCV, ECCV.

Skills

Reinforcement learning

Multimodal AI

PyTorch

Research excellence

Experimental design

Publications in conferences

Education

Master's degree in CS

PhD in ML/NLP/CV

Tools

PyTorch

Job description

Jobgether is seeking an AI Research Engineer (Agentic Reinforcement Learning) based in Ireland. You will conduct advanced research and develop scalable reinforcement learning systems for multimodal AI applications, spanning text, images, audio, and beyond.

The role emphasizes state‑of‑the‑art methods, scalable infrastructure, and robust evaluation. You will publish at top conferences and contribute to globally distributed teams in a fully remote setting.