AI Research Engineer

Job Summary

Driving innovation in multi-modal reinforcement learning, the full-time AI Research Engineer will optimize decision-making across integrated data modalities, develop scalable reinforcement learning techniques, and enhance AI performance in a fully remote environment.

Key responsibilities

• Conduct research on reinforcement learning algorithms for multimodal models and develop unified frameworks integrating multiple modalities
• Design and build reinforcement learning infrastructure for scalable, distributed training while ensuring efficiency and reliability
• Create and curate multimodal simulation environments and datasets to support robust training and evaluation of reinforcement learning systems

Required qualifications

• A Master's degree in Computer Science or a related field is required; a PhD in Machine Learning, NLP, or Computer Vision is preferred
• Proven experience running large-scale reinforcement learning experiments in multimodal systems
• Deep understanding of reinforcement learning algorithms and optimization methods applied to vision and multimodal learning problems
• Strong proficiency in PyTorch and deep learning frameworks for vision and multimodal AI
• Demonstrated ability to apply empirical research to solve core RL challenges in multimodal tasks