Lead Research Innovation Architect

6 days ago

Sukkur, Sindh, Pakistan beBeeMachineLearning Full time $120,000 - $150,000

**Research Innovation Engineer Position**

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At Tether Operations Limited, we drive innovation in architecture development for cutting-edge models of various scales. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field.

About the Role

You will have a deep expertise in video generation model architectures with a hands-on, research-driven approach. Your mission is to explore and implement novel techniques and algorithms that lead to groundbreaking advancements: data curation, strengthening baselines, identifying and resolving existing pre-training bottlenecks to push the limits of model performance.

Responsibilities:
  • Contribute directly to usable prototypes and scalable systems through pioneering multimodal and video-centric research.
  • Design and implement novel AI architectures for multimodal language models, integrating text, visual, and audio modalities.
  • Engineer scalable training and inference pipelines optimized for large-scale multimodal datasets and distributed GPU systems across thousands of GPUs.
  • Optimize systems and algorithms for efficient data processing, model execution, and pipeline throughput.
  • Build modular tools for preprocessing, analyzing, and managing multimodal data assets (e.g., images, video, text).
  • Collaborate cross-functionally with research and engineering teams to translate cutting-edge model innovations into production-grade solutions.
  • Prototype generative AI applications showcasing new capabilities of multimodal foundation models in real-world products.
  • Develop benchmarking tools to rigorously evaluate model performance across diverse multimodal tasks.

For this role, we require a Bachelor's degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience. Expertise in Python & PyTorch, including practical experience working with the full development pipeline from data processing & data loading to training, inference, and optimization, is essential.

Nice to have skills include a PhD in Computer Vision, Machine Learning, NLP, Computer Science, Applied Statistics, or a closely related field, demonstrated expertise in computer vision, video generation foundation model and/or multimodal research, and first-author publications at leading AI conferences such as CVPR, ICCV, ECCV, ICML, ICLR, NeurIPS etc.

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