Member of Technical Staff - Code Generation
Job Description
Introducing Moonlake, AI for creating world simulations.
Overview
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 (e.g., assets, scenes, digital twins) at scale.
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.
What You'll Do
Depending on your strengths and interests, your work may include:
World Modeling
Train models that generate structured interactive environments
Improve multimodal reasoning across vision, language, and simulation
Code Generation Agents
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
Diffusion Rendering
Develop real-time diffusion renderers for stylized game visuals
Improve performance and controllability of video diffusion models
Systems & Infrastructure
Build high-performance training and inference pipelines
Optimize large-scale training and distributed systems
Simulation & Embodied Intelligence
Build environments for training embodied agents
Explore reinforcement learning and multimodal reasoning
What We're Looking For
Strong Signals
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
Technical Skills
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)
Ideal Candidates
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 Francisco.