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Data/Robot Operator Intern (Teleops)(human)

icon building Unternehmen : Neura Robotics
icon briefcase Auftragstyp : Praktikum

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Arbeitsbeschreibung - Data/Robot Operator Intern (Teleops)(human)

In the AI Department, you'll develop the cognitive abilities of our robots, enabling them to understand and interact with their surroundings. You'll work on algorithms that make machines intelligent and adaptive—ranging from object recognition and language processing to decision-making in complex environments. You'll be part of a team that pushes technological boundaries and collaborates closely with software, hardware, and product management teams. Using cutting-edge tools and methods from machine learning and AI, you'll work on projects that have a direct impact on our products. If you're excited about making machines smarter and shaping the future of human-machine interaction, the AI Department is the perfect place for you.

Your mission & challenges

As a Teleoperation Software Engineer, you develop robust, low-latency teleoperation pipelines that enable intuitive and stable control of bimanual robotic systems—including dual-arm and humanoid platforms. Your work supports customer projects, internal developments, demos, trade shows, and exploratory prototypes, and serves as a key enabler for data collection as well as the advancement of autonomy.

  • Design and implement end-to-end teleoperation systems—from human input devices to real-time control of physical robotic systems

  • Map human motion to robotic kinematics across differing morphologies, workspace constraints, and degrees of freedom

  • Develop low-latency, high-performance control loops, including filtering, prediction, and latency compensation strategies

  • Integrate teleoperation with perception systems (vision, depth, force/torque sensing, tactile sensing) for precise and safe manipulation

  • Ensure safe operation through collision avoidance, workspace constraints, compliance control, and fail-safe mechanisms

  • Integrate teleoperation software into existing robotic systems and deploy it on real hardware

  • Collaborate closely with AI and learning teams to enable teleoperation-based data collection for imitation learning and autonomous systems

  • Work with software engineers, project managers, and application teams to define requirements and scalable teleoperation architectures

  • Support customer projects, demos, trade shows, and internal users with system setup, operation, and troubleshooting

What we can look forward to

  • Master’s degree or PhD in robotics, computer science, or a related technical field

  • At least 3 years of hands-on experience developing robotic control or teleoperation systems

  • Strong programming skills in C++ and/or Python, especially in real-time or performance-critical software development

  • Solid experience with ROS (Robot Operating System) and working with real robotic systems

  • Excellent understanding of robot kinematics, coordinate systems, and task-space and joint-space control, particularly for dual-arm systems

  • Experience building low-latency, high-performance software pipelines and debugging timing and synchronization issues

  • Familiarity with human input devices such as VR controllers, motion capture systems, haptic devices, or exoskeletons

  • Experience integrating sensors such as cameras, depth sensors, force/torque sensors, or tactile sensors into control loops

  • Experience with robotics simulation tools (e.g., Isaac Sim, MuJoCo) and cloud systems is a plus

  • High level of ownership when tackling complex tasks, along with strong teamwork skills across software, hardware, and research teams at the system level

  • Very good English skills and good German skills

Original job Data/Robot Operator Intern (Teleops)(human) posted on GrabJobs ©. To flag any issues with this job please use the Report Job button on GrabJobs.
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Über das Unternehmen

Neura Robotics

Cognitive Robotics A new era of human robot collaboration Next-gen robotics for smarter automation Cognitive robots that think and learn, […]

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