プリンシパル・データサイエンティスト
データサイエンティスト正社員リード · 2〜7年—
AIopsソリューションの設計・実装およびAI/MLワークフローの自動化を担当します。コンピュータサイエンス関連の学士または修士号が必須であり、関連分野での2〜7年の実務経験が求められます。Python、FastAPI、Kubernetes、MS Azureのスキルが必須です。チーム規模や報告ラインに関する記載はありません。
AIopsソリューションの設計・実装およびAI/MLワークフローの自動化を担当します。コンピュータサイエンス関連の学士または修士号が必須であり、関連分野での2〜7年の実務経験が求められます。Python、FastAPI、Kubernetes、MS Azureのスキルが必須です。チーム規模や報告ラインに関する記載はありません。
ResponsibilitiesKey Responsibilities:As a AI Ops Expert , Responsible and full ownership for the deliverables with greater defined quality standards with defined timeline and budget Responsibilities:· Design, implement, and manage AIops solutions to automate and optimize AI/ML workflows.· Collaborate with data scientists, engineers, and other stakeholders to ensure seamless integration of AI/ML models into production.· Monitor and maintain the health and performance of AI/ML systems.· Develop and maintain CI/CD pipelines for AI/ML models.· Implement best practices for model versioning, testing, and deployment.· Troubleshoot and resolve issues related to AI/ML infrastructure and workflows.· Stay up-to-date with the latest AIops, MLOps, and Kubernetes tools and technologies.Profile requiredRequirements and skills· Bachelor’s or Master’s degree in Computer Science, Software Engineering, or a related field. · 2-7 year relevant experience· Proven experience in AIops, MLOps, or related fields.· Strong proficiency in Python and experience with FastAPI.· Strong handson expertise on Kubernetes (Or AKS)· Hands-on experience with MS Azure and its AI/ML services, including Azure ML Flow.· Proficiency in using DevContainer for development.· Knowledge of CI/CD tools such as Jenkins, GitHub Actions, or Azure DevOps.· Experience with containerization and orchestration tools like Docker and Kubernetes.· Strong problem-solving skills and the ability to work in a fast-paced environment.· Excellent communication and collaboration skills.Preferred Skills:· Experience with machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn.· Familiarity with data engineering tools like Apache Kafka, Apache Spark, or similar.· Knowledge of monitoring and logging tools such as Prometheus, Grafana, or ELK stack.· Understanding of data versioning tools like DVC or MLflow.· Experience with infrastructure as code (IaC) tools like Terraform or Ansible.· Proficiency in Azure-specific tools and services, such as: · Azure Machine Learning (Azure ML)· Azure DevOps· Azure Kubernetes Service (AKS)· Azure Functions· Azure Logic Apps· Azure Data Factory· Azure Monitor and Application InsightsWhy join usWe are committed to creating a diverse environment and are proud to be an equal opportunity employer. All qualified applicants receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status”.Business insightAt Société Générale, we are convinced that people are drivers of change, and that the world of tomorrow will be shaped by all their initiatives, from the smallest to the most ambitious. Whether you’re joining us for a period of months, years or your entire career, together we can have a positive impact on the future. Creating, daring, innovating, and taking action are part of our DNA. If you too want to be directly involved, grow in a stimulating and caring environment, feel useful on a daily basis and develop or strengthen your expertise, you will feel right at home with us!Still hesitating?You should know that our employees can dedicate several days per year to solidarity actions during their working hours, including sponsoring people struggling with their orientation or professional integration, participating in the financial education of young apprentices, and sharing their skills with charities. There are many ways to get involved.We are committed to support accelerating our Group’s ESG strategy by implementing ESG principles in all our activities and policies. They are translated in our business activity (ESG assessment, reporting, project management or IT activities), our work environment and in our responsible practices for environment protection.