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Mecka AI is building the data infrastructure layer for robotics and embodied AI. The company designs and operates 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.
In this role, you will build the physical systems that researchers use to test what robots have learned. You'll bring together robots, sensors, and software for demonstrations, policy deployment, and experiments that the team can repeat and trust. Your work will focus on precise calibration, sound control, and careful debugging to connect Mecka's data to how robots behave on real hardware, enabling the team to distinguish weaknesses in learned policies from problems in the system running them.
Key responsibilities include:
- Integrating robotics hardware and software for data collection and repeatable experiments
- Developing calibration and diagnostic tools for coordinate frames, timing, and sensor quality
- Deploying perception models and learned policies on robots, and investigating their real-world performance
- Building recording, teleoperation, and evaluation workflows with robot-learning researchers
- Improving system reliability through hardware debugging, software improvements, and clear recovery procedures
You will work closely with frontier robotics teams to bridge real-world data, simulation, learning-based systems, and deployed hardware.
REQUIREMENTS:
- 3+ years of hands-on experience in robotics, mechatronics, or closely related engineering field
- Strong Python and C++ skills with practical experience developing on Linux
- Hands-on experience building, integrating, and debugging robotics or mechatronic systems
- Solid understanding of kinematics, coordinate transforms, sensor calibration, and time synchronization
- Experience with robot interfaces, control loops, and communication between software and physical hardware
- Ability to integrate perception or machine-learning models into a running robotic system
- Systematic approach to diagnosing failures across software, electronics, sensors, and mechanics
