Remote AI Research Engineer - Vision-Language Systems

Winclap; United States; Remoto; USD 180.000 - 280.000; Tempo pieno

Descrizione del lavoro

Tether's AI model team is seeking researchers to drive innovation in training and optimizing vision-language models for real-world deployment. You will lead the full model lifecycle from data curation and training pipelines to evaluation and deployment at scale.

You will collaborate with a compact, high-caliber team to push multimodal learning forward, applying state-of-the-art methods, and publishing findings when applicable; this role offers a global, remote work setup and opportunities to

Competenze

• MS/PhD preferred in CS/ML or related field.
• Proven open-source contributions in multimodal AI.
• Hands-on experience with parameter-efficient fine-tuning and distributed training.

Mansioni

• Conduct end-to-end research and engineering on vision-language models across training, evaluation, and optimization.
• Design post-training pipelines including supervised fine-tuning and knowledge distillation.
• Develop and maintain multimodal datasets with data curation and balancing.
• Improve model efficiency and deployability for resource-constrained environments.
• Build evaluation frameworks to measure performance, robustness, and real-world task success.
• Scale training workflows across distributed GPU infrastructure.
• Identify and resolve bottlenecks in training pipelines to achieve state-of-the-art quality.
• Contribute to open-source ecosystems to accelerate development.
• Stay updated with latest multimodal research and translate findings into practice.
• Publish research findings where applicable.

Conoscenze

Multimodal ML

Vision-language models

Distributed training

Post-training fine-tuning

Reinforcement learning

Knowledge distillation

Data curation

Model evaluation

Formazione

MS/PhD preferred

Strumenti

GitHub

HuggingFace

Descrizione del lavoro

Tether's AI model team is seeking researchers to drive innovation in training and optimizing vision-language models for real-world deployment. You will lead the full model lifecycle from data curation and training pipelines to evaluation and deployment at scale.

You will collaborate with a compact, high-caliber team to push multimodal learning forward, applying state-of-the-art methods, and publishing findings when applicable; this role offers a global, remote work setup and opportunities to