AI​/Robotics Engineer – Learning-Driven Manipulation Agrifood & Industrial Robotics

Eurecat is the second Research & Technology Organisation in Spain and one of the largest applied research and technology transfer organisation in Southern Europe. It brings together the experience of more than 800 professionals who generate an annual turnover of 69 million euros and provides services to more than 2,000 companies. Eurecat integrates advanced digital capabilities and experience in biotechnology, industry and sustainability and collaborates with industry in R+D+I activities and projects, offering advanced scientific and technological services and specialized knowledge to respond effectively to the technological needs of very different business sectors, accelerating innovation, reducing both risks and spendings on scientific and technological infrastructures.

The technology center participates in more than 200 large national and international consortium projects of high strategic R&I, has 230 patents and 10 spin-offs. Eurecat has eleven centers in Catalonia and presence in Madrid, Malaga and Chile.

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.

WHAT WILL YOU DO

If you join the Manipulation team, you will:

Pioneer the next era of learning-driven robotic manipulation

• 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.

Build full AI pipelines, from data to deployment

• 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.

Advance perception for challenging environments

• 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
  .

Make real robots learn and improve

• Integrate your algorithms with our robotic platforms (mobile manipulators, cobots, custom agrifood systems).
• Validate your solutions both in the lab and on field deployments
  .

Collaborate, learn, and grow with us

• 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.

SKILLS & EXPERIENCE

Must-Have

• MSc or equivalent experience in Robotics, AI, Computer Vision, Mechatronics
  , or related fields.
• Practical experience in robotic manipulation, perception, or robot learning (projects, internships, theses, or professional work).
• Strong programming skills in Python and experience with deep learning frameworks (e.g.,
  Py Torch ).
• Experience with ROS or ROS 2, robot control, motion planning, or sensor integration.
• Ability to work both independently and collaboratively in multidisciplinary environments.
• Motivation to build things end-to-end: experimenting, training, and deploying on real robots.

Nice-to-Have

• Knowledge of Transformers, Diffusion Policies, Flow Matching, VLA models, or multimodal robot foundation models.
• Experience in Behaviour Cloning, Imitation Learning, Offline RL, or Deep RL.
• Expe…