Research Engineer, Simulation & World Models

The role

Build simulation systems that train and evaluate robots and embodied agents. You will model physical interactions, create scalable training worlds, and connect simulation with real-world data.

What you will do

• Build simulation environments modeling robots, sensors, objects, contacts, materials and dynamics
• Scale training workloads by building pipelines for parallel rollouts, synthetic data, policy training and evaluation
• Improve physical fidelity by calibrating against measured data
• Drive sim-to-real using system identification, domain randomization and controlled experiments
• Develop world models by building learned dynamics or latent models
• Turn prototypes into reusable simulation assets, training infrastructure and documented methods

Required qualifications

• Deep experience building and debugging physics-based simulation with MuJoCo, Isaac Sim or comparable platforms
• Strong reinforcement learning and embodied AI fundamentals, including observations, actions, rewards and policy evaluation
• Experience with learned dynamics, latent world models or hybrid physics-learning systems
• Strong Python and C++ systems skills
• Ability to design controlled experiments, measure sim-to-real gaps and trace failures

Nice to have

• Simulation or training infrastructure used at scale by a robotics or embodied AI research team
• Demonstrated sim-to-real transfer in manipulation, locomotion, navigation or another physical domain
• Published or open-source work in world models, differentiable simulation, GPU-accelerated simulation or model-based reinforcement learning

Before you apply

• Mecka may use AI-assisted tools to help evaluate applications

About the company

Mecka AI is building the data infrastructure layer for robotics and embodied AI. They design and operate global systems for data capture, data labeling, and hardware-enabled workflows.