Mecka AI is building the data infrastructure layer for robotics and embodied AI.
We partner with leading AI labs and robotics companies to deliver high-quality, real-world datasets used to train, evaluate, and deploy robotic systems. Our work sits directly between research, data, and real-world execution — where model performance is dictated by data quality.
The RoleWe are looking for a Research Scientist, RL & Simulation to own the RL + simulation engine that turns large-scale human demonstrations into scalable robot learning signals.
This is a research-meets-systems role: you’ll build simulation environments, retarget human motion to robot actions, train and evaluate policies, and drive sim-to-real transfer with clear metrics.
What You’ll Work OnSimulation EnvironmentsBuild and maintain simulation environments for robotics learning (e.g., Isaac Sim / Isaac Gym, MuJoCo, Genesis, Habitat, ManiSkill).
Decide what environments and assets to build first to maximize learning velocity.
Convert human demonstrations into robot-executable trajectories.
Explore IK-based, optimization-based, and learning-based retargeting approaches.
Train policies from demonstrations using imitation learning + RL:
Behavior Cloning, DAgger-style aggregation, Offline RL
PPO / SAC (or similar) when online fine-tuning is required
Define evaluation: success metrics, stress tests, generalization, and regression tracking.
Drive transfer via domain randomization, system identification, contact modeling, and failure-mode analysis.
Use real data to identify domain gaps that matter.
MSc/PhD (or equivalent research experience) in robotics, ML, or a related field.
Strong hands-on experience with robot simulation and policy learning.
Proficiency in Python; solid engineering discipline (reproducible experiments, clean code, debugging).
Comfort working end-to-end: environment → data → training → evaluation.
Warning: Research Scientist positions require hyper-specific expertise. Please limit your applications to one research role. Applying to multiple Research Scientist positions suggests a lack of focus and may result in the rejection of all submissions. You may, however, apply to other non-research roles alongside your research application.
Strong Signals:
Experience with manipulation, dexterous hands, or locomotion.
Experience with retargeting, IK, trajectory optimization, or differentiable simulation.
Deep intuition for what makes sim-to-real succeed or fail.
Define how Mecka turns egocentric human behavior into scalable robot learning signals.
High ownership, fast iteration, and direct connection to real-world datasets.
Skills Required
- MSc/PhD (or equivalent research experience) in robotics, ML, or related field
- Hands-on experience with robot simulation and policy learning
- Proficiency in Python and strong engineering discipline (reproducible experiments, clean code, debugging)
- Comfort working end-to-end: environment, data, training, evaluation
- Experience with manipulation, dexterous hands, or locomotion
- Experience with retargeting, IK, trajectory optimization, or differentiable simulation
- Experience with sim-to-real techniques (domain randomization, system identification, contact modeling)
What We Do
Mecka AI is a data and infrastructure company that provides high-quality human movement data to accelerate the development of autonomous systems for humanoid robotics. It serves as the data and deployment layer for physical AI, capturing, structuring, and evaluating real-world activity to create labeled datasets that enable robots to learn and deploy reliably in commercial settings.








