Onsite in Barcelona role - 3 days in the office and 2 days at home
The Senior AI Engineer will develop and deploy key AI products, generating business and scientific insights through advanced data science techniques. This role involves building models using both foundational and cutting-edge methods, processing structured and unstructured data, and collaborating closely with internal stakeholders to solve complex problems in drug development, manufacturing, and supply chain.
Key Responsibilities
Drive the implementation of advanced modelling algorithms (e.g., classification, regression, clustering, NLP, image analysis, graph theory, generative AI) to generate actionable business insights.
Leadership: mentor AI scientists, plan and supervise technical work, collaborate with stakeholders.
Work within an agile framework and in cross-functional teams to align AI solutions with business goals.
Engage internal stakeholders and external partners for the successful delivery of AI solutions.
Continuously monitor and optimize AI models to improve accuracy and efficiency (scalable, reliable, and well-maintained).
Document processes, models, and key learnings & contribute to building internal AI capabilities.
Ensure AI models adhere to ethical standards, privacy regulations, and fairness guidelines.
Key Projects
AI Powered Drug Development - Develop and deploy AI models to optimize drug development processes.
Autonomous Manufacturing - Implement AI-driven solutions to enhance manufacturing efficiencies.
Self-healing Supply Chain - Apply AI techniques to improve supply chain management and logistics.
Qualifications
Required experience:
Bachelor's in operations research, mathematics, computer science, or related quantitative field.
Advanced expertise in Python and familiarity with database systems (e.g. SQL, NoSQL, Graph).
Proven proficiency in at least 3 of the following domains:
Generative AI: advanced expertise working with: LLMs/transformer models, AWS Bedrock, SageMaker, LangChain
Computer Vision: image classification and object detection
MLOps: putting models into production in the AWS ecosystem
Optimization: production scheduling, planning
Traditional ML: time series analysis, unsupervised anomaly detection, analysis of high dimensional data
Proficiency in ML libraries sklearn, pandas, TensorFlow/PyTorch
Experience productionizing ML/Gen AI services and working with complex datasets.
Strong understanding of software development, algorithms, optimization, and scaling.
Excellent communication and business analysis skills.
Nice to have:
Master's or PhD in a relevant quantitative field.
Cloud engineering experience (AWS cloud services)
Snowflake
Software development experience (e.g. React JS, Node JS)
About the Operations IT team: Operations IT is a global capability supporting the Global Operations organization across Pharmaceutical Technology Development, Manufacturing & Global Engineering, Quality Control, Sustainability, Supply Chain, Logistics, and Global External Sourcing and Procurement. Our work directly impacts patients by transforming our ability to develop life-changing medicines, combining cutting-edge science with leading digital technology platforms and data.
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