AI Project Leader (Applied AI for Industry)

Eurecat is one of Europes leading technology centers for accelerating innovation in companies. 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 2000 companies. Eurecat integrates advanced digital capabilities and experience in biotechnology industry and sustainability and collaborates with industry in RDI 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 interested in leading Artificial Intelligence projects that solve real industrial problems and generate measurable value for companies

The Applied Artificial Intelligence Unit at EURECAT is looking for an experienced AI scientist and project leader to lead industrial and R&D projects involving the development validation and deployment of advanced AI and data-driven solutions for the manufacturing sector.

We work at the intersection of advanced AI research and industrial implementation. We collaborate directly with manufacturing companies and other industrial organizations as well as with technology centres universities and partners within competitive national and European R&D programmes.

Our projects address challenges such as Industrial Digital Twins process monitoring quality prediction anomaly detection process optimisation predictive maintenance decision support resource efficiency and increasingly autonomous industrial operations. We work with technologies ranging from Machine Learning Deep Learning and industrial time-series analytics to surrogate modelling physics-informed AI Generative AI LLMs and Agentic AI. Technology selection will always be driven by the industrial problem available data project constraints and expected customer value rather than by the technology itself.

This position has a strong focus on project leadership customer value and industrial applications. We are looking for someone capable of understanding how an industrial operation works identifying where AI can realistically create value structure a technically and economically sound project and leading and participating in its execution towards a successful delivery.

You will be responsible not only for defining and creating technically sound solutions but also for ensuring that projects remain aligned with the customers operational needs expected impact scope schedule and available resources. This requires regular interaction with industrial customers project partners and technical teams. You will help translate operational challenges into feasible AI projects establish priorities manage project execution and ensure that the solutions developed provide tangible value

A strong understanding of AI and data science remains important. You should have sufficient hands-on experience to participate in technical developments and assess technical alternatives challenge technical decisions and understand the limitations and risks of the proposed approaches.

RESPONSABILITIES:

As part of the Applied Artificial Intelligence team your responsibilities will include:

• Project leadership and delivery: Lead AI R&D projects for industrial manufacturing from initial definition through execution validation and final delivery. Coordinate project scope activities resources schedules milestones deliverables dependencies and risks ensuring that projects remain technically feasible and aligned with customer expectations.

• Customer value and impact: Maintain a clear focus on the value generated for customers and partners. Define expected project outcomes and success criteria together with stakeholders and continuously assess whether the technical work is contributing to operational improvements such as increased productivity improved quality reduced scrap production efficiency reduced downtime or better decision-making.

• Industrial and manufacturing problem understanding: Analyse customer processes production environments and operational constraints to understand the real problem behind the initial technical request. Work with plant personnel engineers process experts and management to identify relevant variables available data operational bottlenecks and opportunities for AI-driven improvement.

• AI project definition: Translate industrial and manufacturing needs into realistic data-driven projects defining the use case technical scope required data methodology architecture validation strategy KPIs and implementation roadmap.

• Technical leadership and hands-on: Provide technical direction and contribute to project developments. Review modelling strategies experimental approaches validation methodologies and technical decisions ensuring both scientific quality and industrial applicability.
• Client and partner management: Act as one of the main technical interfaces with industrial customers and project partners. Manage expectations communicate project progress explain technical decisions and limitations facilitate decision-making and maintain alignment between technical activities and operational objectives.

• Technology assessment: Stay up to date with emerging AI technologies and assess their applicability to industrial challenges including advanced Machine Learning Deep Learning time-series modelling GNNs PINNs Generative AI LLMs and Agentic AI.

• Opportunity development: Collaborate with industrial customers business development teams and research partners to identify new project opportunities. Participate in technical discussions with potential customers helping understand their needs and define appropriate project scopes and value propositions.

• R&D proposal development: Contribute to national and European R&D proposals helping transform industrial and manufacturing challenges into ambitious but feasible research and innovation projects. Participate in the definition of technical concepts work packages tasks resources milestones KPIs risks and expected industrial impact.

• Team development: Contribute to the technical growth of the team by sharing knowledge mentoring colleagues and promoting good practices in AI development and project execution.

WORKING ENVIRONMENT AND BENEFITS:

This position is located either in Barcelona (Poblenou) or in Cerdanyola del Vallès near Barcelona (Spain). Besides being well connected to the rest of Europe Barcelona area offers an excellent quality of life and a vibrant technology ecosystem with leading research centres innovative companies active communities and a wide range of events and networking opportunities.

Additionally we offer:

• Permanent contract.

• Hybrid work model (home office and office-based work).

• Flexible working hours shorter Fridays and intensive summer working schedules.

• Flexible remuneration package (health insurance transport meal vouchers training and childcare).

• Professional development through Eurecat Academy courses weekly knowledge-sharing sessions and language training (English Catalan and Spanish).

Academic Background

• Degree in Industrial Engineering Computer Science or Automation Engineering.
• A Masters postgraduate degree or PhD in Artificial Intelligence Data Science Machine Learning Industrial Engineering Automation or Operations.

Required Skills and Experience

• At least 35 years of professional experience combining AI/data-driven projects with industrial manufacturing operational environments.

• Experience managing industrial R&D digitalisation automation or AI projects in manufacturing.

• Demonstrated experience leading technical projects work packages or significant project activities including planning coordination of resources milestones deliverables risks and stakeholder expectations.

• Experience working directly with customers industrial partners or operational teams including requirements gathering project follow-up technical presentations and management of expectations.

• Strong ability to understand industrial manufacturing problems and translate them into feasible technical projects with clearly defined objectives KPIs scope and expected impact.

• Experience or good understanding of industrial operations and manufacturing processes including areas such as production process engineering quality maintenance automation supply chain or continuous improvement.

• Solid knowledge of current and emerging AI technologies including Machine Learning Deep Learning time-series modelling Generative AI LLMs and Agentic AI.

• Ability to balance technical ambition with project constraints including data availability industrial readiness integration effort budget schedule and customer priorities.

• Strong project organisation skills including task prioritisation coordination of multidisciplinary teams risk identification and progress monitoring.

• Strong communication and stakeholder-management skills with the ability to communicate effectively with plant engineers operators data scientists researchers managers and external partners.

• Ability to explain complex AI concepts in terms of business and operational impact rather than exclusively technical performance metrics.

• Critical thinking autonomy pragmatism and willingness to learn about new industrial processes and sectors.

• Professional English and availability to travel when required.