AI Simulation Engineer

Description

Mentee Robotics is redefining humanoid automation with an AI-first approach, integrating cutting-edge perception, reasoning, and dexterous manipulation into a fully autonomous humanoid robot that continuously adapts and learns. Our flagship product, Menteebot v3, is designed to seamlessly integrate into industrial, logistics, and retail environments, performing complex tasks with human-like adaptability.

We are looking for a talented Simulation Engineer to join our Research Team. Simulation is the engine behind our vision, serving as the training ground where our robots learn to walk, manipulate objects, and reason before ever touching the physical world. In this role, you will build the virtual worlds and physical models that enable our AI to bridge the sim-to-real gap, driving the development of the next generation of humanoid robotics.

Responsibilities

• Develop Next-Gen Simulation Frameworks: Architect and maintain scalable simulation pipelines using state-of-the-art platforms (e.g., Isaac Lab/Sim, Newton, MJX) to support end-to-end learning.
• Bridge the Sim-to-Real Gap: Collaborate with AI researchers to design physics-accurate environments for manipulation and locomotion, minimizing the reality gap for Reinforcement Learning (RL) and behavioural cloning (BC) policies.
• Generate Synthetic Data: Create photorealistic and physically consistent synthetic datasets to fuel our perception and reasoning models.
• Build Scalable Assets & Environments: Design and implement diverse simulation scenarios, assets, and procedural environments that test the limits of the robot's autonomy and control algorithms.
• Optimize Performance: Ensure high-throughput parallel simulation to accelerate training cycles, optimizing for GPU-based physics engines.

Requirements

• Educational Background: B.Sc/M.Sc in Computer Science, Robotics, Physics, or a related field.
• Python Proficiency: Strong software engineering skills with extensive experience in Python – a must-have.
• Experience: 2+ years of hands-on experience in robotics simulation, game engine development, or physics programming.
• Math Foundation: Strong background in linear algebra, 3D geometry, and physical modeling.
• Optimisation algorithms: Familiar with different optimisation techniques and frameworks such Bayesian, CMA-ES and Optuna.

Advantages

• Physics Engines: Deep understanding of rigid body dynamics and experience with modern simulators.
• Differentiable Simulation: Experience with differentiable physics engines or GPU-accelerated simulation (e.g., Warp, Taichi).
• ML Frameworks: Experience working with deep learning frameworks, specifically PyTorch.
• Graphics & Rendering: Knowledge of rendering pipelines (Vulkan/OpenGL), USD (Universal Scene Description).