Mlops Engineer

hace 3 semanas

Barcelona, España Astrazeneca Gmbh A tiempo completo

MLOps Engineer Office based in Barcelona.
This is what you will do: The MLOps Engineer reports to the IT Director of Insights and Analytics and is a critical role in Alexion IT RDU organization. You will be a key member of our IT team and play a crucial role in developing and implementing innovative machine learning solutions for our business. Your expertise in MLOps will be critical in designing, building, and deploying production-ready machine learning models at scale.
You will be responsible for: Leading the development and implementation of MLOps infrastructure and tools for machine learning modelsCollaborating with cross-functional teams to identify, prioritize and solve business problems using machine learning techniquesDesigning, developing and implementing production-grade machine learning models that meet business requirementsOverseeing the training, testing, and validation of machine learning modelsEnsuring that machine learning models meet high-quality standards, including scalability, maintainability, and performanceDesign and implement efficient development environments and processes for ML applications.Communicating with stakeholders and senior management to provide updates on the progress of machine learning projectsDeveloping assets, accelerators and thought capital for your practice by providing best in class framework and reusable componentsDeveloping and maintaining MLOps pipelines to automate machine learning workflows and integrating them with existing IT systemsIntegrating Generative AI models based solutions within the broader machine learning ecosystem, ensuring they adhere to ethical guidelines and serve the intended business purposesImplementing robust monitoring and governance mechanisms for Generative AI models based solutions to ensure they evolve in alignment with business needs and regulatory standardsYou will need to have: Bachelor's degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related field4+ years of experience in developing and deploying machine learning models in production environmentsHands-on experience building production models with focus on data science operations including serverless architectures, Kubernetes, Docker/containerization, and model upkeep and maintenanceFamiliarity with API-based application architecture and API frameworks.Experience with CICD orchestration frameworks, such as GitHub Actions, Jenkins or Bitbucket pipelines.Deep understanding of software development lifecycle and maintenance.Extensive experience with one or more orchestration tools (e.g Airflow, Flyte, Kubeflow)Experience working with MLOps tools like experiment tracking, model registry tools and feature stores (e.g MLFlow, Sagemaker, Azure)Strong programming skills in Python and experience with libraries such as Tensorflow, Keras, or PyTorchProficiency in MLOps best practices, including model training, testing, deployment, and monitoringExperience with cloud computing platforms, such as AWS, Azure or GCPStrong understanding of software engineering best practices and agile methodologiesStrong understanding of data structures, algorithms, and machine learning techniquesExcellent communication and collaboration skills with the ability to work in a cross-functional team environmentAbility to work independently and self-driven with strong problem-solving skillsExcellent communication and collaboration skills with the ability to partner well with business stakeholders.We would prefer for you to have: Experience in the pharmaceutical industry or related fieldsAdvanced degree in Computer Science, Electrical Engineering, Mathematics, Statistics, or a related fieldStrong understanding of parallelization and asynchronous computation.Strong knowledge of data science techniques and tools, including statistical analysis, data visualization, and SQL 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 authorization and employment eligibility verification requirements.

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