Job Description
Are you passionate about developing simple, elegant solutions to complex problems? Do you believe that AI has the potential to transform entire industries? If your answer is "Yes" to the above questions, we’d love to have a chat with you about our AI solutions.
As part of the AI Technology group, we seek a MLOps engineer who can contribute to the MLOps framework of our AI platform and the AI solutions built on top of it. We look for someone who is passionate about solving complex business & technical problems by applying best in class engineering, quality, and security practices in the context of the lifecycle management of the AI models that are designed & deployed for external offers or internal functions use cases.
Our MLOps framework will propose a target operating model for ML models, as well as a technical stack to support this operating model, in the cloud and at the edge. It should cover the different steps of the model lifecycle: data preparation, model training, model deployment, model serving, model monitoring & model retraining. Other aspects related to model governance (reproducibility, explainability, traceability) must also be covered.
If you're excited by the opportunity to positively impact business processes through innovation and application of advanced technologies, you will feel at home.
Responsibilities
- Contribute to the definition, architecture, development & maintenance phases of the MLOps technical stack for the AI Hub
- Ensure the development process of this stack follows the DevSecOps recommendations & best practices
- Contribute to the definition of the MLOps operating model and make sure the MLOps stack enforces this model
- Work closely with the other teams from AI Technology group in order to ensure the smooth integration of the MLOps technical stack with the different AI components provided by the group
- Work closely with the different AI Hub teams to refine & confirm the needs related to the MLOps technical stack
- Work closely with the AI DevEx team to guarantee AI delivery quality
Qualifications
- 5+ years of experience in software development
- Strong knowledge of DevOps processes at scale and experience of production systems
- Strong knowledge of AI & ML technologies, as well as ML model management context
- Rigorous mindset, still open to changes
- Good team player
- At ease in an international work environment
- Good understanding of public cloud technologies
- Good understanding of data architecture and data privacy
- Strong notions of cloud and edge security best practices
- Technologies: Github, Python, Azure, AWS, MLFlow, Kubernetes, Terraform
- Familiar with agile methodologies: Scrum, SAFe