About the Role

We’re opening our first ever office in Europe, and looking to hire incredible talent in London to advance our mission of building real-time multimodal intelligence.

Your Impact

• Conduct groundbreaking research in neural network architecture design to advance the state-of-the-art (SOTA) in alternative architectures (e.g., state space models, efficient Transformers, hybrid architectures).

• Design novel architectures that improve model quality, inference efficiency, and adaptability across diverse deployment environments, from cloud to on-device.

• Explore and develop capabilities such as statefulness, long-range memory, and innovative conditioning mechanisms for enhancing model expressiveness and generalization.

• Investigate how architectural decisions impact model trade-offs, including scalability, robustness, latency, and energy efficiency.

• Develop new frameworks and tools to evaluate architectural innovations, benchmarking performance across research and production settings.

• Collaborate with cross-functional teams to translate architectural research into scalable and impactful systems for real-world applications.

What You Bring

• Deep expertise in architecture design, with experience in researching or deploying advanced architectures (e.g., state space models, transformers, RNN variants, CNN variants).

• Strong understanding of how architectures interact with system constraints, including deployment in cloud environments or on-device.

• Proficiency in designing architectures that balance quality, efficiency, and adaptability across different use cases and modalities (e.g., vision, audio, text).

• Familiarity with generative modeling paradigms like autoregressive and diffusion models, and designing capabilities such as statefulness and conditioning in deep learning models.

• A proven research track record in top-tier ML/AI venues (e.g., NeurIPS, ICML, ICLR, CVPR) or demonstrable contributions to state-of-the-art architectures.

• Exceptional analytical and problem-solving skills, with a focus on experimentation and iterative refinement.

• Strong programming skills in deep learning frameworks such as PyTorch or TensorFlow, and experience with profiling tools for understanding model performance.

Nice-To-Haves

• Prior research or publications in state space models, efficient Transformers or other alternative architectures.

• Research or practical experience in designing architectures for multi-modal systems.

• Early-stage startup experience or a track record of rapid innovation in R&D environments.

🏦 401(k)

🦖 Your own personal Yoshi