Research Scientist, RL & Simulation at Mecka AI

Job description

About Mecka AI 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 Role We 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 On Simulation Environments • Build 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. Retargeting (Human → Robot) • Convert human demonstrations into robot-executable trajectories. • Explore IK-based, optimization-based, and learning-based retargeting approaches. Policy Learning & Evaluation • 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. Sim-to-Real • Drive transfer via domain randomization, system identification, contact modeling, and failure-mode analysis. • Use real data to identify domain gaps that matter. Who You Are Required Background • 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. Why This Role • Define how Mecka turns egocentric human behavior into scalable robot learning signals. • High ownership, fast iteration, and direct connection to real-world datasets.