Your impact as a Senior ML Platform Engineer will enable our Client to be a data driven company by helping the business units to deliver high-quality AI components, play a pivotal role in the operational management and continuous development of the Data and Insights Platform, ensuring its reliability and efficiency in enabling rapid AI solutions deployment.

Tasks:

• Lead operational management and continuous development of the platform, aligning with business needs for rapid AI deployment, overseeing strategic planning and execution.
• Install, configure, and manage key platform components, such as Seldon application, Istio, Knative, Elasticsearch, Prometheus, and Grafana. Ensure seamless integration and optimal performance.
• Collaborate closely with the infrastructure team to optimize underlying resources and configurations, ensuring alignment with Seldon and associated ML workloads.
• Develop and enhance application components, including custom Kubernetes operators, contributing to the platform's evolution and extended functionalities. Monitor, troubleshoot, and resolve platform issues, while documenting operational procedures, best practices, and guidelines. Stay updated on Kubernetes and MLOps advancements for continuous innovation and improvement.
• Write and maintain Python code for platform enhancements and custom solutions, operate and maintain the platform in a production environment, ensuring high availability, performance, and security. Provide hands-on MLOps support to data scientists for model deployment.

Requirements:

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field.
• Strong experience in Kubernetes management, with expertise in Seldon being advantageous.
• Proficient in CI/CD, DevOps, application security, and performance monitoring.
• Familiarity with tools like ArgoCD, Crossplane, Istio, Knative, Opensearch, Prometheus, and Grafana.
• Solid understanding of cloud services, preferably AWS, along with experience in maintaining large-scale platforms.
• English: at least B2 level

Preferred Skills and Qualifications:

• Skilled in developing Kubernetes operators and managing complex application integrations.
• Proficiency in Python and/or Go programming.
• Proficiency in MLOps practices and experience supporting data scientists in a machine learning deployment environment.

Offer:

• 100% remote work
• B2B via Experis
• MultiSport Plus
• Group insurance
• Medicover
• E-learning platform