Member of Technical Staff - Simulation Engineer

Embedding VC; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Moonlake in San Francisco is building high-fidelity robotics simulations and world models to advance embodied AI. We’re seeking a hands-on Simulation Engineer to design and implement simulation environments, physics, and sensor models used for robot learning, evaluation, and sim-to-real transfer.

The role collaborates with robotics, world models, and AI teams to ensure scalable, production-quality infrastructure.

Qualifications

• Experience building robotics simulation systems.
• 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.

Responsibilities

• Build robotics simulation environments for training and evaluation.
• Develop scalable simulation workflows for rapid experimentation and learning.
• Improve sim-to-real transfer via calibration and validation.
• Create simulation benchmarks and tooling to support ML workflows.

Skills

Robotics simulation

Python

C++

ROS2

System design

Education

MS or PhD in Robotics

Tools

Isaac Sim

MuJoCo

PyBullet

Gazebo

Drake

ROS2

Job description

Introducing Moonlake, AI for creating world simulations.

About Moonlake

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.

The Role

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.

What You’ll Do

Build Robotics Simulation 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

Improve Sim-to-Real Transfer

• 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

Support Robot Learning

• 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

Build Simulation Infrastructure

• 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

Areas of Focus

Robotics Simulation

• Physics simulation
• Robot dynamics
• Sensor simulation
• Sim-to-real transfer
• Robot learning environments

Simulation Infrastructure

• Synthetic data generation
• Simulation tooling
• Environment automation
• Performance optimization
• Benchmarking and validation

Robotics

• Perception
• Manipulation
• Navigation
• Embodied AI
• Physical reasoning

What We’re Looking For

• 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

Nice to Have

• 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

Why This Role Matters

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.