Machine Learning Research Engineer at RBC Borealis applying ML technology to complex problems with a focus on generative AI, NLP, and time series analysis.
About the role
- AI researcher driving innovation in multimodal and video foundation model architecture at Tether. Engaging in cutting-edge research and development of scalable AI architectures and tools.
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.
Requirements
- 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.
- 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
- First-author publications at leading AI conferences such as CVPR, ICCV, ECCV, ICML, ICLR, NeurIPS etc.
- PhD in Computer Vision, Machine Learning, NLP, Computer Science, Applied Statistics, or a closely related field (Nice to have)
Benefits
- Health insurance
- Flexible work arrangements
- Professional development opportunities
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