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World Model / Action Policy Researcher

Machine Learning Researcher — World Models & Action Policies

Medal enables millions of gamers to capture and share their epic gaming moments and create memories together. Medal users create 3M+ videos per day across over a million daily active users on our desktop and mobile applications. Your work will have a real impact on millions of people around the world!

You'll be working with a talented team of engineers and researchers with a history of building large-scale systems that power creativity and social interaction. Your work will directly contribute to the next generation of intelligent agents and simulation systems that can understand, predict, and act in complex 3D environments.

The majority of your work will focus on designing, training, and evaluating world models and action policies that operate within games and based on gaming data. You’ll experiment rapidly, iterate on architectures, and collaborate closely with our product and engineering teams to bring research ideas to production.

What We're Looking For

  • 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.

  • In-person: Looking to hire in NYC. 5 days in the office.

  • 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.

Our research stack

Core Research: Python, PyTorch, NumPy, Triton, and CUDA
Backend & Infra: Kubernetes, GCP, and large-scale training clusters
Experimentation: We run continuous evaluation, A/B testing, and performance metrics tracking on our deployed models

Why Join Us

  • Work on cutting-edge research that connects AI, gaming, and simulation.

  • Collaborate with a passionate team that values creativity, ownership, and technical depth.

  • Competitive salary, equity options, comprehensive health insurance, and 401k.

  • Opportunity to see your research shape real-world interactive experiences for millions of users.

Average salary estimate

$200000 / YEARLY (est.)
min
max
$160000K
$240000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

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Medal.tv offers an online platform for sharing gameplay clips via the Medal.tv desktop software. Medal.tv was founded in 2017 and is based in the Netherlands.

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Full-time, onsite
DATE POSTED
October 6, 2025
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