Researcher, Model Architecture
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Cartesia
San Francisco, CA (In Person)
Full-Time
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Job Description
Researcher, Model Architecture Cartesia IT San Francisco, CA, USA Posted 6+ months ago Apply now About Cartesia Our mission is to build the next generation of
AI:
ubiquitous, interactive intelligence that runs wherever you are. Today, not even the best models can continuously process and reason over a year-long stream of audio, video and text—1B text tokens, 10B audio tokens and 1T video tokens—let alone do this on-device. We're pioneering the model architectures that will make this possible. Our founding team met as PhDs at the Stanford AI Lab, where we invented State Space Models or SSMs, a new primitive for training efficient, large-scale foundation models. Our team combines deep expertise in model innovation and systems engineering paired with a design-minded product engineering team to build and ship cutting edge models and experiences. We're funded by leading investors at Index Ventures and Lightspeed Venture Partners, along with Factory, Conviction, A Star, General Catalyst, SV Angel, Databricks and others. We're fortunate to have the support of many amazing advisors, and 90+ angels across many industries, including the world's foremost experts in AI. The Role- 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 We'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.
IPS, 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.
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