Join us in shaping the future of AI through cutting-edge data optimization. We’re looking for driven individuals who thrive in fast-changing environments, adapt to new research paradigms, and eagerly take on challenges—whether deploying models, inspecting data, or pioneering new synthetic and reinforcement learning data methods.

Key Responsibilities:

• Develop and implement cutting-edge data strategies to improve the performance, efficiency, and applicability of LLMs, VLMs and Action Models:

  • Generate and augment synthetic multimodal datasets, including images, text, and action trajectories, to advance model capabilities in areas like VQA, agent behaviors, and virtual navigation
  • Apply model distillation techniques to optimize large-scale models for edge deployment, ensuring scalability without compromising performance
  • Design and iterate on evaluation frameworks to target edge cases and measure model improvements across multiple domains
  • Lead research into aligning data with human and AI preferences, implementing feedback loops to refine agent decision-making and learning behaviors
  • Collaborate effectively with cross-functional teams to integrate data-driven solutions into LLM, VLM and Agent systems
  • Stay at the forefront of breakthroughs in AI data strategies, model distillation, and multimodal learning through active scientific exploration

Requirements:

• Technical skills:

  • Strong, polyvalent programming skills in Python covering parallel computing, system design, large-scale deployments, AWS deployments and model evaluations
  • Experience developing and maintaining multimodal data pipelines
  • Experience in training and deploying LLMs, VLMs or Pytorch models

• Research skills:

  • MSc or PhD in machine learning, computer vision, natural language processing, or a related field
  • Deep understanding of training and evaluation paradigms for multimodal models

• Soft skills:

  • Strong communication skills with technical and non-technical staff
  • Effectiveness in fast-changing environments

• Nice to Have:

  • Experience with agent-specific data pipelines and improvement techniques is a plus
  • Experience managing efficient multi-modal human annotation platforms is a plus

Location:

• Paris or London.
• This role is hybrid, and you are expected to be in the office 3 days a week on average.
• Please expect some travel between offices on a reasonable cadence (e.g., every 4-6 weeks).

What We Offer:

• Join the exciting journey of shaping the future of AI, and be part of the early days of one of the hottest AI startups
• Collaborate with a fun, dynamic and multicultural team, working alongside world-class AI talent in a highly collaborative environment
• Enjoy a competitive salary
• Unlock opportunities for professional growth, continuous learning, and career development

If you want to change the status quo in AI, join us.