📋 Context

As a Senior Machine Learning Engineer, you will lead the design, deployment, and optimization of ML/AI models across diverse use cases, from credit scoring to document analysis and generative AI. You’ll also shape best practices, build tools, and act as a key advocate for ML engineering excellence within and outside the organization.

Your responsibilities :

1. Model Deployment and Optimization

• Lead the deployment of ML/AI models in production, ensuring scalability, efficiency, and robustness.

• Automate and monitor inference pipelines, continuously improving performance.

2. Infrastructure and Tools Development

• Architect and maintain scalable ML platforms and pipelines (MLOps) for lifecycle management.

• Develop and integrate CI/CD solutions tailored to ML workflows.

• Optimize cloud resources (primarily Google Cloud Platform) for cost-effectiveness and high performance.

3. Governance and Best Practices

• Define and enforce best practices in model development, testing, monitoring, and governance.

• Ensure traceability, security, and integrity of production models.

• Maintain comprehensive and accessible documentation for tools, processes, and pipelines.

4. Internal Knowledge Sharing and Technology Watch

• Share insights, methodologies, and innovations with internal teams to foster knowledge sharing.

• Lead technical workshops and discussions to promote a strong culture of engineering excellence within the company.

• Stay at the forefront of ML technologies and frameworks through continuous research and exploration.

• Master’s or PhD in Computer Science, Data Science, Applied Mathematics, or a related field.

• 3+ years in Machine Learning Engineering, with proven experience deploying and managing production-grade ML systems.

Hard Skills :

• Advanced expertise in Python and ML frameworks (PyTorch, scikit-learn, etc.).

• Deep understanding of Google Cloud Platform (GCP) and its services (Vertex AI, BigQuery, Cloud Functions).

• Mastery of MLOps practices (CI/CD, Docker, model registry).

• Familiarity with generative AI technologies and large-scale model deployment.

• Strong ability to document and communicate complex technical workflows.

Soft skills :

• Strategic thinking and a focus on impactful, scalable solutions.

• Proactive and autonomous, with a passion for driving technical excellence.

• Collaborative mindset, with the ability to align cross-departmental goals.

• Business acumen and result-oriented approach, with a clear understanding of business challenges and the ability to align technical solutions with strategic objectives.

• A first video chat with Arthur, Talent Acquisition Manager, to get to know each other and tell you more about Younited, our corporate culture & values (30’)

• An Interview with Guillaume, Head of Data to discuss about the role and expectations (60’)

• Online Technical Test

• A Business Case to assess your skills (60’)

• An interview with Julien (Lead Data Scientist) & Robin (Lead Analytics Engineer) (60’)