Embedding VC · San Francisco
Software EngineeringMoonlakeFullTimeposted 6w ago
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, and interactive applications.
We develop the infrastructure that enables intelligent systems to learn, evaluate, and interact within realistic virtual environments before operating in the physical world.
Our work sits at the intersection of:
Robotics
Embodied AI
Interactive 3D Worlds
World Models
Simulation Infrastructure
Physical AI
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, physics, and intelligent behavior.
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 robotics training and simulation to digital twins and interactive environments.
We are looking for exceptional engineers to help build the simulation systems that will power the next generation of robotics and embodied intelligence.
We're looking for a Member of Technical Staff – Simulation Engineer to build the simulation systems and infrastructure that power robotics and embodied AI.
This role focuses on developing high-fidelity simulation environments that accurately model robot behavior, sensors, physics, and real-world interactions. You'll build the simulation infrastructure used for robot learning, evaluation, synthetic data generation, and sim-to-real transfer.
You'll collaborate closely with teams working on robotics, world models, AI systems, and simulation infrastructure.
This is a highly hands-on software engineering role for builders who enjoy solving challenging problems across robotics, simulation, physics, and distributed systems.
Design and develop simulation environments for robotics training and evaluation
Build simulation systems supporting perception, navigation, manipulation, and embodied AI tasks
Develop scalable simulation workflows that enable rapid experimentation and robot learning
Build reusable tooling that makes simulation development efficient and reliable
Compare simulation outputs against real-world robot behavior
Model robot dynamics, sensors, contacts, and environmental interactions
Tune simulation fidelity through calibration and validation
Improve policy transfer using calibration, benchmarking, and domain randomization techniques
Partner with robotics and AI teams to build environments for training and evaluating intelligent systems
Develop infrastructure supporting large-scale synthetic data generation
Create simulation benchmarks for evaluating robotics models
Optimize simulation environments for machine learning workflows
Develop production-quality software supporting simulation systems
Build tools that improve simulation reliability, testing, and scalability
Improve pipelines for simulation creation, execution, and evaluation
Optimize simulation performance while maintaining physical realism
Physics simulation
Robot dynamics
Sensor simulation
Sim-to-real transfer
Robot learning environments
Synthetic data generation
Simulation tooling
Environment automation
Performance optimization
Benchmarking and validation
Perception
Manipulation
Navigation
Embodied AI
Physical reasoning
Experience building robotics simulation systems for robotics, autonomy, embodied AI, or physical AI
Experience with robotics simulators such as Isaac Sim, MuJoCo, PyBullet, Gazebo, Drake, or equivalent
Understanding of robot dynamics, physics simulation, sensor modeling, and sim-to-real transfer
Strong software engineering skills in Python, C++, or similar languages
Experience building production-quality simulation software and infrastructure
Experience writing reliable, maintainable, and well-tested code
Strong systems thinking and problem-solving skills
Ability to work closely with robotics, machine learning, and research teams
Experience with NVIDIA Isaac Sim or Omniverse
Experience generating synthetic data for robotics or machine learning
Experience with domain randomization or procedural environment generation
Familiarity with ROS2 and modern robotics software stacks
Experience optimizing simulation performance or GPU-accelerated simulation
MS or PhD in Robotics, Computer Science, Mechanical Engineering, or a related field
Moonlake's vision depends on simulation systems that allow intelligent agents to learn, evaluate, and improve before operating in the physical world.
The quality of our world models, robotics systems, and AI infrastructure depends on simulation environments that are physically accurate, computationally efficient, and scalable.
As a Simulation Engineer, you'll build the core simulation infrastructure that powers the next generation of robotics and embodied AI.
We are committed to being an on-site, in-person team currently based in San Francisco.