Member of Technical Staff - Code Generation

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 robotics, embodied AI, simulation, gaming, and multimodal agents. We are developing AI-native tooling for creating dynamic worlds where geometry, physics, visuals, audio, and interaction remain coherent in real time.

Our team sits at the intersection of:

• Embodied AI

• Robotics simulation

• Interactive 3D worlds

• World models

• Real-time generation

• AI infrastructure

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.

Depending on your strengths and interests, your work may include:

• Train models that generate structured interactive environments

• Improve multimodal reasoning across vision, language, and simulation
  

• Build agent systems that generate game logic and world structures

• Design tool-using reasoning systems for interactive content generation

• Work on post-training and fine-tuning of code generation models to improve reasoning, tool use, and environment construction
  

• Develop real-time diffusion renderers for stylized game visuals

• Improve performance and controllability of video diffusion models
  

• Build high-performance training and inference pipelines

• Optimize large-scale training and distributed systems
  

• Build environments for training embodied agents

• Explore reinforcement learning and multimodal reasoning
  

• PhD in Computer Science, Machine Learning, Robotics, Graphics, or related field

• Experience working at frontier research labs or leading AI research groups

• Strong publication record or impactful open-source contributions
  

• Deep learning frameworks (PyTorch, JAX, etc.)

• Experience with large-scale training or distributed systems

• Strong coding ability in Python/C++/CUDA

• Experience fine-tuning or post-training large models (especially code generation or multimodal models)
  

• Researchers who want to move quickly from research to product

• Engineers who enjoy building new systems from scratch

• People excited about the intersection of AI + simulation + interactive worlds

We are committed to being an on-site, in-person team currently based in San Mateo