Remote AI Research Engineer - Multimodal Vision-Language

tether; Abu Dhabi; Remote; AED 180,000 - 300,000; Full time

Job summary

Tether is looking for an AI model engineer to drive innovation in training and optimizing vision-language models for real-world deployment. You will work across the full lifecycle—from data curation to model evaluation and optimization—aiming for scalable, production-ready solutions.

You will collaborate with a small, high-caliber team, applying state-of-the-art research to improve model quality and efficiency. A research-driven mindset with strong engineering discipline is essential for success.

Qualifications

• Degree in Computer Science, Machine Learning, or a related field; MS/PhD preferred.
• Strong experience with multimodal post-training workflows including supervised fine-tuning, knowledge distillation, and reinforcement learning from feedback.
• Hands-on experience with parameter-efficient fine-tuning and distributed training frameworks.
• Demonstrated ability to build and improve vision-language models with measurable results on standard benchmarks or real-world tasks.
• Experience adapting models for resource-constrained environments.
• Proven open-source contributions in multimodal AI on GitHub or HuggingFace.
• Publications at top AI conferences (NeurIPS, ICML, ICLR, CVPR, ECCV etc.).

Responsibilities

• Conduct end-to-end research and engineering on vision-language models, covering training, evaluation, and optimization across the full model development lifecycle.
• Design and implement post-training pipelines including supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback.
• Develop and maintain high-quality multimodal datasets, including data curation, filtering, and balancing for domain-specific tasks.
• Drive model efficiency and deployability, adapting models for resource-constrained environments using compression and optimization techniques.
• Design and implement evaluation frameworks and benchmarks to measure model performance, robustness, and real-world task success.
• Build and scale training workflows across distributed GPU infrastructure.
• Identify and resolve bottlenecks in training pipelines to achieve state-of-the-art model quality on target benchmarks.
• Contribute to and leverage open-source ecosystems including models, datasets, and tooling to accelerate development.
• Stay current with the latest research in multimodal learning and vision-language systems, translating relevant findings into practical improvements.
• Publish research findings in top-tier AI conferences and journals where applicable.

Skills

Multimodal post-training workflows

Knowledge distillation

Reinforcement learning from feedback

Parameter-efficient fine-tuning

Distributed training frameworks

Resource-constrained adaptation

Open-source contributions

Publications in AI conferences

Education

MS/PhD preferred

Job description

Tether is looking for an AI model engineer to drive innovation in training and optimizing vision-language models for real-world deployment. You will work across the full lifecycle—from data curation to model evaluation and optimization—aiming for scalable, production-ready solutions.

You will collaborate with a small, high-caliber team, applying state-of-the-art research to improve model quality and efficiency. A research-driven mindset with strong engineering discipline is essential for success.