EU Jobs

Researcher, Models (UK)

London•Remote
May 6, 2026
Full Time Permanent
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Deadline date:

Job Description

About the Company

This organisation is building next-generation artificial intelligence systems designed to learn from and interact with the world in a more human-like way.
Its founding team emerged from the Stanford AI Lab, where early breakthroughs were made in State Space Models (SSMs)—a class of architectures aimed at improving the efficiency and scalability of large foundation models.

The company combines:

  • Advanced research in neural architecture design
  • High-performance systems engineering
  • Product-focused AI development for real-world deployment

Backed by major global investors, the organisation operates across San Francisco, London, and Bangalore, with a strong emphasis on rapid experimentation, research excellence, and shipping production-grade AI systems.
Relevant European research and governance frameworks supporting this type of work include:

Role Overview

The team is expanding into Europe and is hiring an AI Research Engineer / Neural Architecture Specialist in London to support cutting-edge work in real-time multimodal intelligence systems.
This role focuses on designing and improving foundational neural architectures that underpin next-generation AI models.

Key Responsibilities

In this role, you will:

Research and design novel neural network architectures to advance state-of-the-art AI systems

Develop efficient model structures such as:

  • State space models
  • Advanced Transformer variants
  • Hybrid and multimodal architectures

Improve model performance across:

  • Accuracy and generalisation
  • Inference speed and latency
  • Energy efficiency and scalability

Investigate architectural features such as:

  • Long-term memory mechanisms
  • Stateful reasoning systems
  • Advanced conditioning methods for multimodal inputs
  • Build evaluation frameworks for benchmarking model performance in both research and production environments
  • Translate research prototypes into scalable systems deployed across cloud and edge devices
  • Collaborate closely with engineering and product teams to bring innovations into production

Research Focus Areas

This role sits at the intersection of deep learning research and systems engineering, with emphasis on:

  • Efficient deep learning architectures
  • Multimodal AI (text, vision, audio)
  • Generative modelling systems
  • Trade-offs between speed, cost, and performance
  • Real-time inference systems
  • Scalable AI deployment pipelines

Candidate Profile

The ideal candidate will have deep expertise in neural architecture design and a strong research-oriented mindset.
You should have:

  • Strong background in machine learning, deep learning, or AI systems
  • Experience with architectures such as Transformers, RNNs, CNNs, or state space models
  • Familiarity with generative modelling approaches (autoregressive, diffusion-based systems)
  • Strong programming skills in PyTorch or TensorFlow
  • Experience working with model profiling, optimisation, and performance tuning
  • Ability to balance theoretical research with practical deployment constraints

Research Experience

Applicants should ideally demonstrate:

  • Publications or contributions in top-tier AI/ML venues such as NeurIPS, ICML, ICLR, or CVPR
  • Experience working on large-scale AI systems or cutting-edge model development
  • Evidence of innovation in architecture design or model efficiency improvements

Nice to Have

  • Experience with multimodal AI systems (text, image, audio integration)
  • Prior work on efficient or alternative neural architectures
  • Startup or fast-paced R&D environment experience
  • Strong record of rapid prototyping and iterative research development

Working Environment

The organisation operates in a high-speed research and engineering culture, where:

  • Rapid experimentation is encouraged
  • High technical standards are maintained
  • Research is expected to translate into production impact
  • Collaboration between researchers and engineers is continuous
  • The London office is part of a global, in-person engineering culture that values daily collaboration and knowledge sharing.

Benefits Overview

Employees typically receive:

  • Competitive base salary with equity participation
  • Commuter support allowance
  • Flexible paid time off policy
  • Daily meals and refreshments
  • Collaborative in-office working environment
  • Relocation and visa sponsorship support (case-dependent)

Relevant UK and EU employment and digital policy frameworks include:

Additional Notes

  • The company prioritises research speed, technical excellence, and real-world deployment impact
  • Work is primarily in-person across global offices
  • Visa sponsorship may be available depending on role and location requirements
  • Strong emphasis on collaboration between research, engineering, and product teams

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