Member of Technical Staff - Robotics & Simulation

Embedding VC • San Francisco, CA

13d • Onsite

About The Position

Introducing Moonlake, AI for creating world simulations. Moonlake is building the frontier of AI-powered world simulation. We create systems that generate, simulate, and reason over rich 3D environments for robotics, embodied AI, and interactive applications. Our platform enables the creation of digital worlds, synthetic environments, and scalable simulation infrastructure used to train the next generation of intelligent systems. Our work sits at the intersection of: Robotics, Physical AI, World Models, Simulation Infrastructure, Synthetic Data Generation, Embodied Intelligence. Moonlake has raised $28M in seed funding from NVIDIA Ventures, Threshold Ventures, AIX Ventures, and notable angels including Naval Ravikant and Jeff Dean. Our mission is to build the foundational infrastructure that enables robots to learn, reason, and operate effectively in the physical world.

Requirements

• Strong background in robotics, embodied AI, machine learning, or related fields
• Experience working with physical robotic systems
• Experience with robotic simulation platforms such as Isaac Sim, MuJoCo, Habitat, Gazebo, or similar
• Familiarity with robot learning, foundation models, or world models
• Strong software engineering skills in Python and robotics tooling
• Experience deploying software onto real robotic hardware
• Ability to debug across hardware, software, and machine learning systems
• Comfort working in a fast-moving research and engineering environment

Responsibilities

• Evaluate Robot Foundation Models & Policies: Benchmark and evaluate robot foundation models in simulated environments, Design evaluation frameworks for robotic reasoning, planning, manipulation, and navigation, Measure generalization, robustness, and task performance across diverse scenarios, Build infrastructure for large-scale simulation-based testing and validation.
• Train World Models for Robotics: Develop and train world models that enable robots to understand and predict environment dynamics, Build systems that learn from multimodal robot data including vision, depth, state, and actions, Improve environment understanding, forecasting, and decision-making capabilities, Work closely with simulation and AI teams to advance robotic world modeling systems.
• Build Real-World Robot Learning Pipelines: Collect and curate real-world robotics datasets, Train and fine-tune models using both simulated and physical robot data, Improve sim-to-real transfer for robotic policies and world models, Develop workflows connecting simulation, training infrastructure, and deployed robotic systems.
• Deploy and Operate Physical Robots: Set up, integrate, and maintain robotic hardware platforms, Bring learned policies and world models onto real robotic systems, Debug hardware, software, sensing, and control issues, Develop deployment pipelines for testing, validation, and continuous improvement, Work directly with robotic manipulators, mobile robots, sensors, and compute systems.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: No Education Listed