Mecka AI
Research Engineer, Simulation & World Models
$170K–$300K
New York +1 · Hybrid · Full-time · Posted Oct 7, 2026
- Location
- New York
San Francisco
About the job
Build and scale physics-based robot simulation and learned or hybrid world models for training, evaluating, and transferring embodied agents to real-world systems.
What you'll do
- Build simulation environments that model robots, sensors, objects, contacts, materials, and dynamics.
- Develop scalable pipelines for parallel rollouts, synthetic data, policy training, and evaluation; improve fidelity and sim-to-real transfer.
- Build learned or hybrid world models for prediction, planning, and control, and turn prototypes into reusable tools.
What they ask for
- Deep experience building and debugging physics-based simulation with MuJoCo, Isaac Sim, or comparable platforms.
- Strong reinforcement learning and embodied AI fundamentals.
- Experience with learned dynamics, latent world models, or hybrid physics-learning systems.
- Strong Python and C++ systems skills, with ability to build scalable, reproducible tools.
Nice to have
- Simulation or training infrastructure used at scale by a robotics or embodied AI research team.
- Demonstrated sim-to-real transfer, or published/open-source work in world models, differentiable or GPU-accelerated simulation, or model-based reinforcement learning.
Pay
$170K – $300K (base salary)
Tools
MuJoCo, Isaac Sim, Python, C++
AI focus
Develop and use learned or hybrid world models and simulation to train, evaluate, and improve prediction, planning, control, and sim-to-real transfer for robots and embodied agents.
Model-written summary · the original posting is authoritative