Role
: Senior Robotics Engineer (Robot Learning & Manipulation) 📍 Full-Time | Permanent
Location
: Various location in Germany
Build the Future of Intelligent Robotics
THRYVE is partnering with a world-leading robotics company pushing the boundaries of robot learning, dexterous manipulation, and real-world autonomy.
We're looking for a
Senior Robotics Engineer
who thrives at the intersection of robotics, machine learning, and human-robot interaction. You'll help develop next-generation robotic systems that learn from human demonstrations and operate reliably in complex, unstructured environments.
This is an opportunity to work on cutting-edge manipulation challenges, leveraging teleoperation, imitation learning, and state-of-the-art AI to create robots capable of performing increasingly sophisticated real-world tasks.
What You'll Do
-
Architect and develop robot learning pipelines for large-scale, high-quality data collection and training.
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Design and integrate advanced teleoperation systems, including force-feedback, haptics, and multimodal sensory interfaces.
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Advance robotic manipulation capabilities, with a particular focus on dexterous robotic hands and learning from human demonstrations.
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Collaborate closely with world-class AI researchers, roboticists, and software engineers to move cutting-edge research into deployed systems.
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Contribute to the full lifecycle of robotic learning systems, from data acquisition and model development through to real-world deployment and validation.
What We're Looking For
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Strong expertise in robot learning, teleoperation, imitation learning, and human-in-the-loop robotics.
-
Understanding of
Vision-Language Models (VLMs)
,
Vision-Language-Action (VLA) architectures
, and their application to embodied AI and robotic manipulation.
-
Deep understanding of manipulation, control systems, and real-world robotic deployment challenges.
-
Advanced programming skills in
C++
and
Python
.
-
Hands-on experience with
ROS / ROS2
and modern robotics software stacks.
-
Experience developing and deploying robotic systems beyond simulation.
Highly Desirable
-
Diffusion-based policies and generative models for robotics.
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Learning from Demonstration (LfD) or Reinforcement Learning.
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VR/AR-based teleoperation interfaces.
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Unity, Isaac Sim, MuJoCo, or similar simulation environments.
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Experience working with dexterous hands, tactile sensing, or embodied AI systems.