Senior Research Engineer - Multimodal & Video Foundation Model (100% Remote)

Tether Operations Limited; Remote; CAD 100,000 - 125,000; Full time

Job summary

A technology firm is seeking a talented AI model architect in Ottawa, Canada. The role involves pioneering multimodal and video-centric research, designing scalable training pipelines, and prototyping generative AI applications. Ideal candidates should have a Bachelor's degree in Computer Science, deep expertise in video generation models, and proficiency in Python & PyTorch. The position offers opportunities to collaborate with cross-functional teams to drive innovation and develop cutting-edge model solutions.

Qualifications

• Bachelor's degree in Computer Science or related field.
• Deep expertise in video generation model architectures.
• Expertise in Python & PyTorch, including the full development pipeline.
• Experience with large-scale text data or interleaved data.
• Hands-on experience in development or benchmarking LLMs or related models.

Responsibilities

• Pioneer multimodal and video-centric research for usable prototypes.
• Design AI architectures for multimodal language models.
• Engineer scalable training and inference pipelines for large datasets.
• Optimize systems for efficient model execution.
• Build tools for preprocessing and managing multimodal data.
• Collaborate to translate innovations into production solutions.
• Prototype generative AI applications showcasing new capabilities.
• Develop benchmarking tools to evaluate model performance.

Job description

About the job

As a member of the AI model team, you will drive innovation in architecture development for cutting‑edge models of various scales, including small, large, and multi‑modal systems. Your work will enhance intelligence, improve efficiency, and introduce new capabilities to advance the field.

Responsibilities

• Pioneer multimodal and video‑centric research that moves fast and breaks ground, contributing directly to usable prototypes and scalable systems.
• 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.

Qualifications

• Bachelor’s degree in Computer Science, Computer Engineering, or a related technical field, or equivalent practical experience.
• Deep expertise in video generation model architectures with a hands‑on, research‑driven approach.
• Expertise in Python & PyTorch, including practical experience working with the full development pipeline from data processing & loading to training, inference, and optimization.
• Experience working with large‑scale text data, or (bonus) interleaved data spanning audio, video, image, and/or text.
• Direct hands‑on experience in developing or benchmarking at least one of the following topics: LLMs, Vision Language Models, Audio Language Models, generative video models.

Nice to have skills

• 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.
• First‑author publications at leading AI conferences such as CVPR, ICCV, ECCV, ICML, ICLR, NeurIPS, etc.

Important information for candidates

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