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Researcher, Models (UK)

  • London, ON, Canada

Full-time

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Job details

Job type
Full-time
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Posting language
English
Posted

Original job description

Cartesia is a pioneering company focused on architecting AI that learns and interacts like humans. They are seeking a Researcher in Models to conduct groundbreaking research in neural network architecture design and collaborate with cross-functional teams to translate architectural research into impactful systems.

Responsibilities

  • 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
More about this job

Responsibilities

Conduct research and design novel neural network architectures, including state space models, efficient Transformers, and hybrid architectures, to improve model quality, efficiency, and adaptability. Develop evaluation frameworks and collaborate with cross-functional teams to translate architectural research into scalable systems for real-world applications.

Requirements

The role calls for expertise in neural network architecture research and the ability to investigate trade-offs involving scalability, robustness, latency, and energy efficiency. It also requires developing and benchmarking architectural innovations and collaborating across teams to bring research into production systems.

Skills

  • State Space Models
  • Efficient Transformers
  • Hybrid Architectures
  • Model Quality Optimization
  • Inference Efficiency
  • Model Adaptability
  • Statefulness
  • Long-Range Memory
  • Conditioning Mechanisms
  • Model Generalization
  • Scalability
  • Robustness
  • Latency Optimization
  • Energy Efficiency
  • Benchmarking

Visa sponsorship

Not detected in the job text

Categories

  • Science & Research
  • Technology
  • Software
  • Engineering

Keywords

  • Artificial Intelligence
  • Neural Networks
  • Neural Network Architecture
  • State Space Models
  • Efficient Transformers
  • Hybrid Architectures
  • Model Quality
  • Inference Efficiency
  • Cloud Deployment
  • On-Device Deployment
  • Statefulness
  • Long-Range Memory
  • Conditioning Mechanisms
  • Model Expressiveness
  • Generalization
  • Scalability
  • Robustness
  • Latency
  • Energy Efficiency
  • Evaluation Frameworks
  • Benchmarking
  • Research
  • Production Systems
  • Cross-Functional Collaboration

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