About The Position

Mecka AI is building the data infrastructure layer for robotics and embodied AI. We design and operate global systems for data capture, data labeling, and hardware-enabled workflows used by leading AI labs and robotics companies to train and validate humanoid and embodied AI systems. We work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware. Build simulation systems that train and evaluate robots and embodied agents. Model physical interactions, create scalable training worlds and connect simulation with real-world data across Mecka Labs. This is a hands-on research engineering role for someone exceptional in simulation, physics and learning. You'll work with MuJoCo, Isaac Sim and related tools, close sim-to-real gaps, and build learned or hybrid world models for prediction, planning and control. You own whether the simulated world behaves credibly and runs at scale; partner roles turn it into trainable tasks and reliable evaluations.

Requirements

  • 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; you build scalable, reproducible tools other researchers can extend.
  • Design controlled experiments, measure sim-to-real gaps and trace failures to models, data, policies or infrastructure.

Nice To Haves

  • 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.

Responsibilities

  • Build simulation environments: Model robots, sensors, objects, contacts, materials and dynamics, with scenarios grounded in real behavior.
  • Scale training workloads: Build reliable pipelines for parallel rollouts, synthetic data, policy training and evaluation.
  • Improve physical fidelity: Calibrate against measured data, find mismatches in dynamics or sensing and make targeted improvements.
  • Drive sim-to-real: Use system identification, domain randomization and controlled experiments to improve transfer.
  • Develop world models: Build learned dynamics or latent models, combine them with physics-based systems and test their value for prediction, planning and control.
  • Build with the team: Turn prototypes into reusable simulation assets, training infrastructure and documented methods with researchers and engineers.

Benefits

  • Inclusive Hiring at Mecka
  • Should you require any accommodation whatsoever during the interview process, please inform us without any hesitation.
  • Mecka is dedicated to ensuring equal treatment and opportunity in all phases of recruitment, selection, and employment, in compliance with employment law.
  • We do not discriminate based on gender, race, religion, national origin, ethnicity, disability, gender identity/expression, sexual orientation, veteran or military status, or any other protected category.
  • Mecka is proud to be an equal opportunity employer, fostering a culture of inclusivity and maintaining a work environment that is free from discrimination, harassment, and retaliation.
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