World Model Lead

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Vacancy Overview

Application Open:

Full-Time

Job Purpose:

You will own the end‐to‐end strategy, design, and delivery of our general-purpose world modeling efforts. You’ll translate cutting-edge research (e.g., the PAN framework) into robust, production-ready simulators, guide a multidisciplinary team of engineers and scientists, and ensure alignment with IFM’s mission.

 

Key Responsibilities:

  • Technical Leadership & Vision
    • Define and evolve the overall world model architecture, drawing on the PAN principles:
      1. Multimodal data ingestion
      2. Mixed continuous/discrete representations
      3. Hierarchical generative modeling with an enhanced LLM backbone and diffusion-based predictors
      4. Generative loss grounded in real observations
      5. Simulation for RL-based agent training
    • Establish performance, safety and evaluation benchmarks, driving continuous improvement.
  • Project & Team Management
    • Oversee planning, resourcing, and timeline for world model projects.
    • Manage research engineers and scientists (e.g., data curators, RL experts, simulator devs) to achieve unified progress.
  • Cross-Functional Collaboration
    • Partner with agent, reasoning, and deployment teams to integrate world model outputs into downstream applications (robotics, multi-turn dialogue, autonomous systems).
    • Liaise with external collaborators (academia & industry) to incorporate the latest advances and tooling.
  • Governance & Communication
    • Report project status, risks, and key insights to senior leadership and stakeholders.
    • Champion best practices in reproducibility, documentation, and knowledge sharing.

Required Qualifications:

  • Ph.D. or M.S. with 8+ years in AI research or engineering, specializing in world modeling, simulation, or generative modeling.
  • Proven track record building large-scale simulators or predictive models for complex environments.
  • Deep expertise in transformer-based LLMs, diffusion models, and hierarchical latent representations.
  • Hands-on experience with reinforcement learning frameworks (policy learning, planning with latent dynamics).
  • Strong leadership skills: project management, cross-site coordination, and team mentorship.

Preferred Qualifications:

  • Experience leading multi-location technical teams in fast-paced R&D settings.
  • Published contributions to world model architectures or simulation benchmarks.
  • Track record of taking research prototypes into production systems.

 

Apply Now:

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