Associate Principal Ai Engineer

hace 2 meses

Barcelona, España Astrazeneca A tiempo completo

.Onsite in Barcelona role - 3 days in the office and 2 days at homeThe 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 ResponsibilitiesDrive 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 ProjectsAI 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.QualificationsRequired 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, LangChainComputer Vision: image classification and object detectionMLOps: putting models into production in the AWS ecosystemOptimization: production scheduling, planningTraditional ML: time series analysis, unsupervised anomaly detection, analysis of high dimensional dataProficiency in ML libraries sklearn, pandas, TensorFlow/PyTorchExperience 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)SnowflakeSoftware development experience (e.G

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