Responsibilities
- 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.
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.
Nice to Have
- Publications in top-tier venues demonstrating your expertise in multimodal AI research.
- Experience in writing efficient GPU kernels using CUDA, optimising performance for multimodal tasks.
Work Arrangement
Remote (Worldwide) — Toronto, San Francisco, London, New York, Paris, Montreal, Seoul, Germany
Additional Information
- Cohere is remote-friendly.
- For those in the office: a daily lunch program, plenty of snacks, and regular community and social events.
- For those not near an office: a co-working benefit so you can work alongside others in your city.
- Everyone receives a $500 home office stipend to set up your workspace properly.
- We may use AI-enabled tools to screen and assess applicants against the criteria for this position.
- Beware of Scams: Cohere will never ask for payment or third-party services (e.g., CV writing) as part of our hiring process.
- All legitimate roles are listed on the Cohere careers page and LinkedIn only, with all communications from Cohere employees coming from an @cohere.com or @cw.cohere email alias.
