Lead Software Engineer - MLOps Engineer

Job Description: ML OPS Engineer (LEAD)

You will be responsible for building, operating, and evolving the Data Science Delivery Platform (DSDP), enabling Data Scientists and Engineers to develop, deploy, and scale AI/ML solutions securely and efficiently. You will work closely with Data Science teams, infrastructure teams, and business stakeholders to maintain and evolve a reliable, self-service AI platform.

Key Responsibilities

• Build and maintain scalable platform services on Kubernetes.
• Build and maintain tools to facilitate the end-to-end data science lifecycle, covering experimentation, deployment, monitoring, and governance.
• Support and enhance enterprise AI tools such as Dataiku, MLFlow, Snowflake, and Spark.
• Implement automation, CI/CD pipelines, and platform engineering best practices.
• Ensure platform reliability, observability, security, and compliance.
• Provide technical support and enablement for Data Scientists and Data Engineers.
• Continuously improve platform capabilities and user experience.

Technical Environment

• Infrastructure: Kubernetes, Docker, Linux
• AI/ML: Dataiku, MLFlow, Kedro, Jupyter Notebooks
• Data: Snowflake, PostgreSQL, Spark, Hadoop
• Development: Python, FastAPI, SQLAlchemy, PyTest
• DevOps: GitHub Actions, Jenkins, Ansible, Terraform, Harbor, JFrog
• Observability: Grafana, Kibana, Elasticsearch, Zabbix

Required Skills

• Strong hands-on experience with Kubernetes and container technologies; debugging platform issues and operational anomalies in Kubernetes environments is a core day-to-day responsibility
• Strong server administration expertise across Linux environments, system operations, networking, performance troubleshooting, access management, and infrastructure reliability
• Practical Python development skills for platform automation, operational tooling, integration, and troubleshooting activities
• Hands-on experience with Terraform for infrastructure provisioning, configuration management, and infrastructure-as-code automation
• Experience building and maintaining CI/CD pipelines using GitHub Actions, Ansible, Jenkins, and related platform automation frameworks
• Good understanding of MLOps practices, AI/ML lifecycle management, model deployment, and Data Science workflows
• Knowledge of monitoring, observability, troubleshooting, and platform operations to ensure service reliability and operational continuity
• Experience with Dataiku, MLflow, or similar AI/ML platforms is required

Soft Skills

• Customer-focused and collaborative mindset – You will have to interact with data scientists and support them with platform issues on a day-to-day basis.
• Strong ownership and problem-solving abilities.
• Ability to communicate effectively with technical and non-technical stakeholders.
• A drive for innovation, simplification, and continuous improvement.  

Preferred Experience

• 8+ years in Platform Engineering and MLOps Engineering.
• Experience supporting enterprise AI/ML platforms at scale.
• Exposure to GenAI/LLMOps technologies is a plus.

At 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