Cartesia is hiring a Researcher: Multimodal to join our team in London. You will conduct research to advance AI across audio, text, vision, and other modalities, focusing on novel algorithms and models for multimodal understanding and generation.

What You'll Do

Conduct research at the intersection of machine learning, multimodal data, and generative modeling.
Develop novel algorithms for multimodal understanding and generation, leveraging new architectures, training algorithms, datasets, and inference techniques.
Design and build models that enable seamless integration of modalities for multimodal reasoning on streaming data.
Lead the creation of robust evaluation frameworks to benchmark model performance on multimodal datasets and tasks.
Collaborate closely with cross-functional teams to translate research breakthroughs into impactful products and applications.

What We're Looking For

Expertise in machine learning, multimodal learning, and generative modeling, with a strong research track record in top-tier conferences.
Proficiency in deep learning frameworks such as PyTorch or TensorFlow, with experience in handling diverse data modalities.
Strong understanding of state-of-the-art techniques for multimodal modeling, such as autoregressive and diffusion modeling, and deep understanding of architectural tradeoffs.
Passion for exploring the interplay between modalities to solve complex problems and create groundbreaking applications.
Excellent problem-solving skills, with the ability to independently tackle research challenges and collaborate effectively with multidisciplinary teams.

Nice to Have

Experience working with multimodal datasets, such as audio-visual datasets, video-captioning datasets, or large-scale cross-modal corpora.
Background in designing or deploying real-time multimodal systems in resource-constrained environments.
Early-stage startup experience or experience working in fast-paced R&D environments.