AI Research Engineer (Agentic Reinforcement Learning)
Jobgether (company site, opens in a new tab)RemoteDirect career pageEst. 30–55 LPA
Posted 13h ago
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Job description
Structured overview of role & requirements
About This Role
- Develop and research advanced reinforcement learning algorithms for complex multimodal AI systems involving images, text, and audio.
- Design and implement scalable training infrastructure and reward modeling strategies to enhance autonomous agent performance, stability, and alignment.
- Conduct rigorous experimentation, benchmarking, and evaluation to optimize policy performance and publish findings at top-tier international AI conferences.
Minimum Requirements
- Master's degree in Computer Science or related discipline; PhD preferred in Machine Learning, NLP, Computer Vision, or related field.
- Demonstrated experience with large-scale reinforcement learning experiments in multimodal and vision-centric AI systems.
- Proven research publication record in top AI conferences such as ICML, NeurIPS, ICLR, CVPR, ICCV, or ECCV.
- Advanced proficiency in PyTorch and deep learning frameworks with hands-on experience in building end-to-end reinforcement learning pipelines.
Ideal Candidate Profile
- Strong background in reinforcement learning theory and practical optimization in high-dimensional, multimodal environments involving vision and audio.
- Experienced in designing scalable, distributed training systems and robust evaluation frameworks for autonomous AI agents.
- Track record of advancing AI research through empirical experimentation and contributing research outputs to leading international forums.