Robotics Software Engineer, Teleoperation
Mecka
About Mecka AIMecka 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.
The roleYou’ll take arms we buy off the shelf and make them safely, precisely controllable by an operator thousands of kilometers away. Many of these arms ship with no teleop stack and no teleop input device, so you’ll choose and integrate the operator hardware, write the mapping from human motion to robot motion, and own everything that runs on the robot. You’ll also be the person who makes sure every frame of data we record is correctly timestamped and synchronized.
What you’ll do
Integrate new commercial arms and grippers: vendor SDKs, drivers, calibration, and a common control interface.
Evaluate and integrate operator input devices (leader arms, VR controllers, 6-DoF mice, haptics).
Write and tune inverse kinematics and Cartesian/joint controllers for high DOF robotic arms for teleoperation and manipulation.
Design for latency you can’t remove: local safety limits, workspace and collision constraints, graceful handling of dropped or late packets, and safe stop when the link degrades.
Prototype shared‑autonomy features (assisted grasping, motion smoothing, task‑level primitives) that make long‑distance teleop faster and less tiring.
Own sensor integration: cameras, depth, wrist cams, joint state, force/torque. Get time synchronization right across all of them.
Work with a Teleop Platform Engineer on the end‑to‑end latency budget and on what we record, at what rate, in what format.
Go to robot sites when needed to bring up hardware and debug in person.
What we’re looking for
3+ years writing production level software that runs real robot hardware (arms strongly preferred), in industry or a serious research lab.
Strong in C++ and/or Python;
comfortable with Linux,real‑time considerations, and debugging at the hardware boundary.
Solid grasp of manipulator kinematics: forward/inverse kinematics, Jacobians, singularities, joint limits, and at least one way of doing Cartesian control well.
Experience with a robotics middleware stack (e.G., ROS 2) or a good reason you chose not to use one.
You’ve integrated a robot from a vendor SDK, not just in simulation.
Comfortable owning safety‑relevant code and being careful about it.
Nice to have
Built a teleoperation system before, especially over unreliable or long‑distance networks.
Experience with impedance/admittance control, force feedback, or haptics.
Familiarity with robot learning data: demonstration collection, imitation learning, episode formats.
Experience with motion planning libraries, simulation, or calibration tooling.
Some networking or systems performance experience: you can read a packet capture and profile a control loop.
Experience with VR/XR
If you don’t check every box above but believe you can do the job, we encourage you to apply — we’re looking for capability and trajectory, not a perfect checklist match.
We strive to create an inclusive work environment for all;
we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, we will partner with you to meet your needs.
We may use AI‑assisted tools to help evaluate applications against the requirements of this role. These tools support our recruiting team in identifying qualified candidates but do not replace human judgment or limit which applications may be reviewed or considered.
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The roleYou’ll take arms we buy off the shelf and make them safely, precisely controllable by an operator thousands of kilometers away. Many of these arms ship with no teleop stack and no teleop input device, so you’ll choose and integrate the operator hardware, write the mapping from human motion to robot motion, and own everything that runs on the robot. You’ll also be the person who makes sure every frame of data we record is correctly timestamped and synchronized.
What you’ll do
Integrate new commercial arms and grippers: vendor SDKs, drivers, calibration, and a common control interface.
Evaluate and integrate operator input devices (leader arms, VR controllers, 6-DoF mice, haptics).
Write and tune inverse kinematics and Cartesian/joint controllers for high DOF robotic arms for teleoperation and manipulation.
Design for latency you can’t remove: local safety limits, workspace and collision constraints, graceful handling of dropped or late packets, and safe stop when the link degrades.
Prototype shared‑autonomy features (assisted grasping, motion smoothing, task‑level primitives) that make long‑distance teleop faster and less tiring.
Own sensor integration: cameras, depth, wrist cams, joint state, force/torque. Get time synchronization right across all of them.
Work with a Teleop Platform Engineer on the end‑to‑end latency budget and on what we record, at what rate, in what format.
Go to robot sites when needed to bring up hardware and debug in person.
What we’re looking for
3+ years writing production level software that runs real robot hardware (arms strongly preferred), in industry or a serious research lab.
Strong in C++ and/or Python;
comfortable with Linux,real‑time considerations, and debugging at the hardware boundary.
Solid grasp of manipulator kinematics: forward/inverse kinematics, Jacobians, singularities, joint limits, and at least one way of doing Cartesian control well.
Experience with a robotics middleware stack (e.G., ROS 2) or a good reason you chose not to use one.
You’ve integrated a robot from a vendor SDK, not just in simulation.
Comfortable owning safety‑relevant code and being careful about it.
Nice to have
Built a teleoperation system before, especially over unreliable or long‑distance networks.
Experience with impedance/admittance control, force feedback, or haptics.
Familiarity with robot learning data: demonstration collection, imitation learning, episode formats.
Experience with motion planning libraries, simulation, or calibration tooling.
Some networking or systems performance experience: you can read a packet capture and profile a control loop.
Experience with VR/XR
If you don’t check every box above but believe you can do the job, we encourage you to apply — we’re looking for capability and trajectory, not a perfect checklist match.
We strive to create an inclusive work environment for all;
we welcome applicants from all backgrounds and are committed to providing equal opportunities. Should you require any accommodations during the recruitment process, we will partner with you to meet your needs.
We may use AI‑assisted tools to help evaluate applications against the requirements of this role. These tools support our recruiting team in identifying qualified candidates but do not replace human judgment or limit which applications may be reviewed or considered.
#J-18808-Ljbffr
Vacancy posted 3 hours ago
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