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AI/Robotics Engineer – Learning-Driven Manipulation for Agrifood & Industrial Robotics
Job summary
A leading technology center in Cataluña is seeking a passionate engineer or researcher to drive advancements in AI-powered robotic manipulation. The role involves developing complex manipulation policies, integrating advanced AI techniques, and advancing perception in challenging environments. Ideal candidates will have a degree in Robotics or AI and possess skills in machine learning and data collection. Join us to innovate in the fields of agriculture and advanced manufacturing within a collaborative international team.
Qualifications
- Experience with dexterous manipulation policies in unstructured environments.
- Strong understanding of AI algorithms and data collection techniques.
- Proficiency in training models for robotic applications.
Responsibilities
- Develop dexterous manipulation policies for Agrifood and Manufacturing.
- Lead data curation and multimodal dataset preparation.
- Deploy models optimizing for real-time performance.
Skills
Education
Tools
Are you excited about shaping the next generation of AI-powered robotic manipulation in real, unstructured environments?
The Robotics and Automation Unit at Eurecat Technology Center (Barcelona) is looking for a passionate engineer or researcher who wants to push the boundaries of robot learning, dexterous manipulation, and perception-rich autonomy in agriculture and advanced manufacturing.
You’ll join a multidisciplinary team working at the intersection of robotics, AI, and real-world deployment, contributing to systems that harvest fruit, manipulate objects in factories, and learn robust skills through data and experience.
If you join the Manipulation team, you will:
- Develop dexterous manipulation policies for complex, uncertain environments in both Agrifood and Manufacturing.
- Integrate Transformers, VLAs, Diffusion Policies, Flow Matching, Foundation Models for Robotics (RT-X style), and Imitation Learning into real robot systems.
- Design and execute data collection campaigns in real environments (greenhouses, orchards, industrial settings).
- Lead data curation, annotation pipelines, dataset augmentation, and multimodal dataset preparation (RGB-D, proprioception, tactile, force-torque data).
- Train behaviour cloning, reinforcement learning, and foundation-model-prompted RL/IL.
- Deploy learned models on-robot / on the edge, optimizing for latency, reliability, and real-time performance under field conditions.
- Develop 3D perception, crop/fruit detection, pose estimation, grasp synthesis, and scene understanding for unstructured natural environments.
- Fuse vision, proprioception, and force data to enable safe physical interaction.
- Integrate your algorithms with our robotic platforms (mobile manipulators, cobots, custom agrifood systems).
- Validate your solutions both in the lab and on field deployments.
- Work with an international consortium of companies, R&D partners, and farmers/growers.
- Contribute to scientific publications, demos, project deliverables, and client interactions.
- Participate in project planning, execution, and new proposal definition.
* The salary benchmark is based on the target salaries of market leaders in their relevant sectors. It is intended to serve as a guide to help Premium Members assess open positions and to help in salary negotiations. The salary benchmark is not provided directly by the company, which could be significantly higher or lower.