Researcher, Models

Job summary

Responsibilities

Conduct groundbreaking research in neural network architecture design to advance the state-of-the-art 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 they're looking for

• 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.

Tech stack

• Databricks
• Transformers
• PyTorch
• TensorFlow