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Moonlake is seeking a Product Engineer to join our on-site San Francisco team. You will own full-stack development from concept to shipped features using React, Next.js, TypeScript, and Python as needed, balancing product judgment with engineering excellence.
Join a mission to build world-building, embodied AI tools and AI infrastructure for researchers, developers, and creators. You will collaborate across research, engineering, and founders to ship fast, iterate on usage, and influence product
Introducing Moonlake, AI for creating world simulations.
Moonlake is building the frontier of interactive world models: systems that generate, simulate, and reason over 3D environments for embodied AI, robotics, and gaming. We develop the simulation infrastructure to build worlds—including assets, scenes, and digital twins—at scale.
Our work sits at the intersection of:
Moonlake is building the next generation of AI infrastructure for interactive digital worlds. Our mission is to enable anyone to create, simulate, and interact with rich environments using natural language and multimodal inputs—turning simple ideas into worlds with structure, logic, and agents that can perceive and act.
Our team has raised $28M in seed funding from NVIDIA Ventures, Threshold Ventures, AIX Ventures, and notable angels including Naval Ravikant and Jeff Dean to build the foundational layer for the future of AI—powering everything from creative tools and games to robotics training, simulations, and digital twins. Our goal is to make building and experimenting with these environments as accessible and scalable as publishing video on the internet.
We are looking for exceptional research engineers and applied researchers to help push the frontier of interactive AI.
We're looking for a Product Engineer who combines strong full-stack engineering with sharp product judgment and a bias for shipping.
We want someone who can:
Moonlake is building products that sit at the intersection of AI systems and human creativity, simulation and interaction, and research infrastructure and product experience.
The interface layer is critical. As AI systems become increasingly capable, the challenge is no longer just building better models—it's making those capabilities intuitive, responsive, and effortless to use.
You'll help define how researchers, developers, and creators interact with the next generation of world-building and embodied AI tools.
Experience in any of the following is a plus, but not required:
We are committed to being an on-site, in-person team currently based in San Francisco.