AI Research Engineer, Multimodal Reinforcement Learning at Tether

Role overview

The AI model team researches multimodal reinforcement learning for decision making and adaptive behaviour. This role develops training algorithms and infrastructure for models that work with text, images and audio, including constrained hardware settings. The posting lists Hanoi, Vietnam.

Responsibilities

• Research reinforcement-learning algorithms for multimodal and vision-centric models, including diffusion and autoregressive approaches.
• Build training infrastructure and reward models for large-scale experiments and improve training stability.
• Curate simulation environments and multimodal datasets, then evaluate policy performance across tasks.
• Investigate reward hacking, sample inefficiency and optimisation bottlenecks; test alternative learning strategies.

Qualifications

• A master’s degree in computer science or related field; a PhD in machine learning, NLP or vision is preferred.
• Large-scale multimodal or vision reinforcement-learning experiments with measurable policy improvements.
• Deep knowledge of RL optimisation, exploration and sample efficiency in high-dimensional settings.
• PyTorch and end-to-end simulation, training, evaluation and deployment work, with a research publication record.

About Tether

Tether develops digital-token products, including USDT, alongside projects in peer-to-peer communications and AI. The employer describes a globally distributed remote team.

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