Position Expired
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Senior Member of Technical Staff (Multimodal AI)
Cohere
Requirements
- Possess exceptional software engineering skills, with a proven track record of building robust and scalable systems,
- Have a strong command of Python and are well-versed in popular deep learning frameworks like JAX, PyTorch, and TensorFlow, with an understanding of their multimodal capabilities,
- Knowledge of distributed training strategies, especially for large-scale multimodal models,
- Familiarity with autoregressive models, particularly their application in multimodal tasks such as image or video captioning, speech-to-text generation,
- Bonus: Publications in top-tier venues demonstrating your expertise in multimodal AI research,
- Bonus: Experience in writing efficient GPU kernels using CUDA, optimising performance for multimodal tasks,
- Have a deep passion for machine learning and its potential to impact various industries through multimodal applications,
- Enjoy tuning and optimising large multimodal models, and have experience building evaluations to measure their performance,
- Are comfortable diving into complex ML codebases to identify and resolve issues, ensuring the smooth operation of our systems,
- Thrive in a fast-paced, technically challenging environment, where you can contribute your innovative ideas and solutions,
- Have a history of delivering creative, practical solutions to real-world problems, demonstrating your ability to think outside the box
What the job involves
- At Cohere, we believe in the power of multimodal AI to revolutionise the way we interact with technology,
- Our engineering teams push the boundaries of what's possible, and we're looking for talented individuals to join us on this exciting journey. With an exceptional ratio of compute resources to engineers, we provide an ideal environment for you to explore, innovate and shape the future of AI,
- Design and develop cutting-edge multimodal AI systems, integrating various modalities such as text, speech, and vision,
- Conduct research and experiments on our advanced compute infrastructure, exploring novel ideas in multimodal representation learning, transfer learning, and more,
- Collaborate closely with our world-class teams, learning from and contributing to their expertise in the field
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