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Associate Principal AI Engineer

Lieu Barcelone, Catalogne, Espagne Job ID R-209806 Date de publication 11/04/2024

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.
• Autonomus 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. We operate from key hubs in the UK, Sweden, the US, China, and our Global Technology Centers in India and Mexico. 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.



AstraZeneca embraces diversity and equality of opportunity. We are committed to building an inclusive and diverse team representing all backgrounds, with as wide a range of perspectives as possible, and harnessing industry-leading skills. We believe that the more inclusive we are, the better our work will be. We welcome and consider applications to join our team from all qualified candidates, regardless of their characteristics. We comply with all applicable laws and regulations on non-discrimination in employment (and recruitment), as well as work authorisation and employment eligibility verification requirements.

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