AI Research Engineer (Multi-Modal & Vision)
About the role
Tether is looking for an AI Research Engineer to work on its multimodal AI research team, focusing on vision-language models, RLHF, and multimodal architectures. The role involves designing and training large-scale VLMs, implementing RLHF pipelines, and advancing the state of the art in visual understanding, image reasoning, and cross-modal alignment. This is a deeply technical research engineering position at the intersection of ML research and production deployment.
What you'll do
- Design, train, and fine-tune vision-language models (VLMs) at scale using self-supervised and RLHF-based approaches.
- Develop and maintain high-quality multimodal training data pipelines (image-text pairs, grounding, visual QA).
- Implement and optimize RLHF pipelines including reward modelling, PPO/DPO, and Constitutional AI methods for vision models.
- Research and prototype novel architectures for cross-modal alignment and visual reasoning.
- Collaborate with inference and deployment teams to bring research models to production.
Requirements
- Strong background in deep learning with hands-on experience in vision-language model training (ViT, CLIP, BLIP-2, LLaVA, or similar).
- Proficiency in PyTorch; experience with large-scale distributed training on GPU clusters.
- Familiarity with RLHF/RLAIF techniques applied to multimodal models.
- Strong mathematical foundation in optimization, probability, and linear algebra.
- Demonstrated research output: publications, open-source contributions, or equivalent proof of advanced ML work.
About Tether Operations Limited
Tether Operations Limited is the company behind USDT, the world's largest stablecoin by market cap. Tether funds and operates a research division (Tether Data) focused on AI, with projects spanning LLMs, vision-language models, and open-source AI infrastructure.
Visit Tether Operations Limited→
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