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Medal · 2 days ago

World Model / Action Policy Researcher

New York, NY

Full-time

Onsite

Senior Level

$350K/yr - $450K/yr

5+ years exp

Medal is a leading platform for gaming moments, focused on advancing human-like intelligence in machines. The World Model / Action Policy Researcher will conduct cutting-edge research in deep learning and reinforcement learning, particularly in the context of gaming and simulation environments.

GamingOnline GamesVideo GamesVideo Streaming

Responsibilities

5+ years of experience in deep learning research or reinforcement learning, with a focus on embodied agents or simulation environments

Strong foundation in representation learning and generative modeling, particularly using architectures such as diffusion models, VAEs, and transformers applied to video

Experience with world models and predictive control — you understand how to train models that simulate dynamics and plan actions in learned environments

Proficiency in reinforcement learning (RL, model-based RL, or imitation learning) and the ability to design and evaluate policy networks

Programming fluency in Python and deep learning frameworks such as PyTorch

Strong experimental skills — comfort with large-scale training, evaluation pipelines, and managing complex datasets or simulations

Publications or open-source contributions in areas like world modeling, simulation learning, or agent policies are a strong plus

Ownership & scientific rigor: You see ideas through from concept to proof to deployment. You write clean, reproducible code and maintain a high bar for experimental validity

Performance and scaling mindset: You care about how research translates into production systems, with an understanding of compute efficiency, distributed training, and data bottlenecks

Curiosity-driven and result-oriented: You’re excited by open-ended problems, but you also know how to define measurable goals and ship impactful systems

Gaming & simulation passion: Interest in interactive environments, physics-based simulations, or gaming AI. Experience with Unity, Unreal Engine, or custom simulators is a plus

Qualification

Deep learning researchReinforcement learningRepresentation learningGenerative modelingPython programmingPyTorchWorld modelsPredictive controlExperimental skillsGaming passionCuriosity-drivenScientific rigorResult-orientedOwnership

Required