Contribute to designing and delivering secure, efficient, and scalable platform for machine learning.
Develop, implement, and maintain efficient and scalable CI / CD processes.
Build system to support real-time model monitoring, anomaly detection, and version management.
Collaborate with Data Science teams to implement MLOps practices on the cloud platform, including pipeline automation, versioning, CI / CD, and test automation.
Optimize infrastructure for cost efficiency and support Data Science teams in optimizing solution costs.
Provide support in troubleshooting and incident management for ML pipelines.
Work with enterprise architects and owners of other systems to integrate ML solutions hosted on the Analytics Platform with business systems, including BPMN.
Develop standards and best practices for using and integrating the Analytics Platform.
Ensure compliance with security and data governance policies.
requirements-expected :
Min 3 years of professional experience in MLOps / ML Engineering, with knowledge of best practices in software development, including CI / CD / CT.
Proficiency and experience in the Azure cloud environment and Databricks, including configuration and maintenance as an ML platform.
Advanced programming skills, especially in languages such as Python and SQL. Experience with R is a plus.
Solid understanding of the ML model lifecycle (from training to deployment, monitoring, and decommissioning).
Hands-on experience in building models and implementing the machine learning lifecycle at scale in complex environments. Practical experience in designing and working with a Feature Store. Experience with testing in the ML process.
Proficiency in containerization and orchestration technologies, including Docker and Kubernetes.
Practical knowledge of MLFlow, REST APIs, and Spark.
Familiarity with tools and processes related to version control, CI / CD, and automation.
Experience with Terraform is a plus.
Experience in AI projects is a plus.
Strong analytical and communication skills, and the ability to work in interdisciplinary teams.
offered :
Employment based on employment contract or B2B
Flexible starting hours
Possibility of full remote work or hybrid model
Attractive employee benefits package : private medical care (Luxmed), subsidy for Multisport card, additional benefits tailored to your needs within the cafeteria system, group insurance for employees on preferential terms
Opportunity to receive an attractive bonus in the employee referral program
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